Methods of selecting treatment options for cancer

Abstract

Disclosed herein is a method of treating cancer in a subject in need thereof. The method comprises determining a first level of a first cancer-specific antigen in a cancer sample of the subject; determining a second level of a second cancer-specific antigen in the cancer sample; and administering to the subject a first antibody-drug conjugate (ADC) targeting the first cancer-specific antigen or a second ADC targeting the second cancer-specific antigen based on the levels of the two cancer-specific antigens. Also disclosed herein is a method of constructing a cancer antigen level standard, which can be used in the selection of ADCs.

Description

METHODS OF SELECTING TREATMENT OPTIONS FOR CANCERCROSS-REFERENCE TO RELATED APPLICATIONSThe present application claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 63 / 535,619, filed August 31, 2023, which is incorporated herein by reference in its entirety.REFERENCE TO AN ELECTRONIC SEQUENCE LISTINGThe XML file named "047162-7478WO1 Sequence Listing.xml" created on August 06, 2024, comprising 3,690 bytes, is hereby incorporated by reference in its entirety.BACKGROUNDCancers are sometimes treated by targeted therapies in which specific genes and proteins that help cancer cells survive and / or grow, or unique to or overexpressed in cancer cells, are targeted by one or more drugs. A large category of drugs used in targeted therapies are antibody drug conjugates (ADCs). Currently, there are over 300 potential antibody drug conjugates (ADCs) under study as potential targeted therapy in oncology. An ADC is often able to precisely deliver higher dosage of toxic chemotherapy to target protein expressing cancer cells than can be tolerated in the chemotherapy’s unconjugated form. Its mechanism of action is thought to be dependent on the recognition of the antibody target triggering chemotherapeutic uptake into the cells leading to high specificity as a mechanism to bring highly toxic drugs only to cells expressing the target. This approach increases the effective dose while reducing toxicity. Examples of ADCs include Trastuzumab deruxtecan (T-DXd) and Sacituzumab govitecan (SG), which are early approvals both currently used in treating metastatic breast cancer.In treating cancers, it is desirable to use the most effective drug first. The identification of the most effective drug, however, is often a difficult task in practice. In the advanced setting, there is often a lack of companion diagnostic tests. However, it is in the patients’ interest to know if they are likely to benefit.Therefore, there is a need for novel and effective methods for assessment of ADC targets as well as to determine which ADC should be selected for a patient. The present study addresses this need.SUMMARYIn some aspects, the present invention is directed to the following non-limiting embodiments:Method of treating cancerIn some aspects, the present invention is directed to a method of treating cancer in a subject in need thereof.In some embodiments, the method comprises: determining a first level of a first cancerspecific antigen in a cancer sample of the subject; and determining a second level of a second cancer-specific antigen in the cancer sample.In some embodiments, the method further comprises administering to the subject a first antibody-drug conjugate (ADC) targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value.In some embodiments, the method further comprises administering to the subject a first antibody-drug conjugate (ADC) targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value, and the second level is equal to or lower than a second predetermined value.In some embodiments, the method further comprises administering to the subject a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value.In some embodiments, the method further comprises administering to the subject a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.In some embodiments, the first level, the first predetermined value, and / or the third predetermined value are expressed as absolute levels of the first cancer-specific antigen.In some embodiments, the second level, the second predetermined value, and / or the fourth predetermined value are expressed as absolute levels of the second cancer-specific antigen.In some embodiments, the first level, the first predetermined value, and / or the third predetermined value are expressed as a percentile rank of the levels of the first cancer-specific antigen in a collection of samples of the cancer.In some embodiments, the second level, the second predetermined value, and / or the fourth predetermined value are expressed as a percentile rank of the level of the second cancerspecific antigen in the collection of samples of the cancer.In some embodiments, the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.In some embodiments, the first level and / or the second level is determined by a quantitative immunofluorescence method or a quantitative chromogenic method.In some embodiments, the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines the first level and the second level in a same immunostaining assay.In some embodiments, the cancer is breast cancer.In some embodiments, the first cancer-specific antigen is human epidermal growth factor receptor 2 (HERZ), and / or the second cancer-specific antigen is tumor associated calcium signal transducer 2 (TROP2).In some embodiments, the method further comprises collecting the cancer sample from the subject.In some embodiments, the subject is a human.Method of predicting cancer treatment outcomes or Method of in vitro examination of the sampleIn some aspects, the present invention is directed to a method of predicting an outcome of a treatment of a cancer with a sample from the cancer.In some aspects, the present invention is directed to a method of performing an in vitro examination of the sample.In some embodiments, the method comprises: determining a first level of a first cancerspecific antigen in the sample; and determining a second level of a second cancer-specific antigen in the sample.In some embodiments, the method further comprises making a prediction that the cancer is more susceptible to a first ADC targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value.In some embodiments, the method further comprises making a prediction that the cancer is more susceptible to a first ADC targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value and the second level is equal to or lower than a second predetermined value.In some embodiments, the method further comprises making a prediction that the cancer is more susceptible to a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value.In some embodiments, the method further comprises making a prediction that the cancer is more susceptible to a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.In some embodiments, the first level, the first predetermined value, and / or the third predetermined value are expressed as absolute levels of the first cancer-specific antigen.In some embodiments, the second level, the second predetermined value, and / or the fourth predetermined value are expressed as absolute levels of the second cancer-specific antigen.In some embodiments, the absolute levels are expressed as amount per area as determined by a quantitative imaging methodIn some embodiments, the absolute levels are expressed as attomole / mm2.In some embodiments, the first level, the first predetermined value, and / or the third predetermined value are expressed as a percentile rank of the levels of the first cancer-specific antigen in a collection of samples of the cancer.In some embodiments, the second level, the second predetermined value, and / or the fourth predetermined value are expressed as a percentile rank of the level of the second cancerspecific antigen in the collection of samples of the cancer.In some embodiments, the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.In some embodiments, the first level and / or the second level is determined by a quantitative immunofluorescence method or a quantitative chromogenic method.In some embodiments, the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines the first level and the second level in a same immunostaining assay.In some embodiments, the cancer is breast cancer.In some embodiments, the first cancer-specific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancer-specific antigen is human trophoblast cell-surface antigen (Trop2).In some embodiments, the method further comprises collecting the sample from a subject.In some embodiments, the subject is a human.Method of constructing cancer antigen level standardIn some aspects, the present invention is directed to a method of constructing a cancer antigen level standard in a cancer type.In some embodiments, the method comprises determining the levels of a first cancerspecific antigen in a collection of cancer samples of the cancer type.In some embodiments, the method further comprises plotting a frequency distribution of the first cancer-specific antigen levels such that each given level of the first cancer-specific antigen corresponds to a percentile rank of the first cancer-specific antigen levels.In some embodiments, the method further comprises determining the levels of a second cancer-specific antigen in the collection of cancer samples.In some embodiments, the method further comprises plotting a frequency distribution of the second cancer-specific antigen levels such that each given level of the second cancer-specific antigen corresponds to a percentile rank of the second cancer-specific antigen levels.In some embodiments, the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.In some embodiments, the levels of the first cancer-specific antigen and / or the levels of the second cancer-specific antigen are determined by a quantitative immunofluorescence method or a quantitative chromogenic method.In some embodiments, the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines a first level of the first cancerspecific antigen and a second level of the second cancer-specific antigen of a given sample in the collection of cancer samples in a same immunostaining assay.In some embodiments, the cancer type is breast cancer.In some embodiments, the first cancer-specific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancer-specific antigen is human trophoblast cell-surface antigen (Trop2).BRIEF DESCRIPTION OF THE DRAWINGSThe following detailed description of exemplary embodiments will be better understood when read in conjunction with the appended drawings. For the purpose of illustrating, nonlimiting embodiments are shown in the drawings. It should be understood, however, that the instant specification is not limited to the precise arrangements and instrumentalities of the embodiments shown in the drawings.Fig. 1 illustrates two antibody-drug conjugates (ADCs) used to treat breast cancer according to some embodiments. Trastuzumab deruxtecan targets HER2 (Nakada et al., Chem Pharm Bull (Tokyo). 2019;67(3): 173-185) and sacituzumab govitecan targets TROP2.Fig. 2 demonstrates that breast cancer patients having amplification of HER2 (all patients shown have either 3+ or 2+ HER2 amplification) generally respond to trastuzumab deruxtecan treatment, in accordance with some embodiments. Data from DESTINY-BreastOl clinical trial (Modi et al., N Engl J Med. 2022 Jul 7;387(l):9-20).Figs. 3A-3D demonstrate that lower levels of expression (1+) of HER2 protein in breast cancer patients corresponds to lower response to trastuzumab deruxtecan treatment when compared to higher expression (2+) of HER2. Data from the phase 2 DAISY trial (Mosele et al., Nat Med. 2023 Aug;29(8):2110-2120).Figs. 4A-4B demonstrate that breast cancer with higher TROP2 expression (Fig. 4B, H- score 100) respond better to an ADC targeting TROP2 (sacituzumab govitecan) when compared to breast cancer having lower TROP2 expression (Fig. 4A, H-score < 100), in accordance with some embodiments. Note that the H-score<100 shows that the 95% confidence interval (CI) around the Hazard Ratio (HR) is greater than 1.0 showing that the relationship is not significant whereas for the H-Score>100 the upper bound of the 95% CI is 0.83 meaning that the SG treated patients had a statistically significant better outcome than the TPC control group.Fig. 5 shows the analysis of expression of HER2 and TROP2 protein in a collection of breast cancer samples, in accordance with some embodiments. The expression levels were determined with singleplex quantitative assays, and no correlation between HER2 and TROP2 expressions was identified. The percentile ranking of the expression levels of each biomarker are shown for selected cases to illustrate that one target may be substantially higher than the other in any given patient.Figs. 6A-6E show that the multiplex “troplex” assay (the term “troplex” used to refer to a non-limiting embodiment herein which assays multiple antigens including TROP2) is highly concordant with the singleplex assessment of each target protein, HER2 (Fig. 6B) and TROP2 (Fig. 6C) in a population of breast cancer patients (Figs. 6A-6C) and in cancer cell lines (Figs. 6D-6E).Fig. 7A-7D show the test of the multiplex quantitative assay herein on some cancer cell lines that may be used to standardize the fluorescent signal to amol / mm2units, in accordance with some embodiments.Figs. 8A-8C show the dynamic range of both HER2 and TROP2 target antigen levels constructed from a breast cancer sample collection, in accordance with some embodiments.Fig. 9 illustrates the difference in HER2 and TROP2 expression in some samples of the breast cancer sample collection. This illustrates that some cases are higher for HER2 (red) and other cases are higher for TROP2 (yellow).Fig. 10 is an overview of quantitative high-sensitivity HER2 & TROP2 multiplex immunofluorescence assay according to some embodiments.Figs. 11A-1 IE illustrate certain aspects of TROP2 antibody optimization, validation, and standard curve, in accordance with some embodiments. Fig. 11 A: Titration of anti-Trop2 antibody clone 2151 with the assay detection system demonstrated 0.1 ug / mL resulted in thelargest si nal-to-noise ratio using the breast cancer test array (YTMA 263, 80 tissue cores). Noise and signal were defined as the bottom 15% and top 15% of scores by Qymia score across conditions, respectively. Figs. 1 IB-11 C : Trop2 expression (Qymia score) from clone 2151 correlates strongly with two other anti-Trop2 antibody clones (Fig. 1 IB) SP295 and (Fig. 11C) EPR20043. These Trop2 antibody clones recognize the extracellular domain of Trop2. Figs.1 ID-1 IE: Example of calibration curve on CMA with 2 replicates per cell line using optimal Trop2

[2151] antibody concentration and fluorescence detection system. Fig. 1 IE is the calibration curve using the subset of cell line standards tested that are within the linear range of the assay.Figs. 12A-12G illustrate some aspects of the validation of Troplex multiplex high- sensitivity HER2 & TROP2 assay, in accordance with some embodiments. Fig. 12A: Overview of TMA staining results for experiment combing primary antibodies HER2 [29D8] and TROP2

[2151] into a multiplex assay. Figs. 12B-12C: Singleplex HER2 and TROP2 expression on breast cancer test array demonstrates strong correlation to multiplex “Troplex” assay expression (in Qymia score). Figs. 12D-12E: Inter-assay results of HER2 and TROP2 expression quantified in 386 breast cancer cases across 3 separate TMAs using Troplex assay. Figs. 12F-12G: Interoperator results of HER2 and Trop2 expression quantified in 49 breast cancer TMA spots.Figs. 13A-13E illustrate the quantification of HER2 and TROP2 expression in unselected breast cancer cohort of 323 cases, in accordance with some embodiments. Fig. 13A: HER2 expression barplot in 323 unselected, serial breast cancer cases (YTMAs 489, 499) with assay LOD and LOL. Fig. 13B: TROP2 expression barplot in 323 unselected, serial breast cancer cases (YTMAs 489, 499) with assay LOD and LOL. Fig. 13C: Scatterplot of TROP2 vs. HER2 expression in cohort. Weak to no correlation observed between HER2 and TROP2 expression (Pearson r = -0.17, p = 0.0014, n = 323). The sectors drawn by the LOQ and LOL of the biomarkers highlights subgroups, including HER2-negative / TROP2-expressors and TROP2- negative / HER2-expressors subgroups. Figs. 13D-13E: HER2 and TROP2 expression across clinical receptor status of breast cancer cohort and additional TNBC cohort (n=404). Box and whisker plots are shown with lower and upper dashed lines indicating LOQ and LOL of respective targets for multiplex assay. Mann-Whitney U test used for statistical testing, with p- value < 0.05 indicated by asterisks.Figs. 14A-14E are representative results of HER2 and TR0P2 staining, in accordance with some embodiments. Fig. 14A: Case with HER2 and TROP2 expression both below LOQ. Fig. 14B: Case with high TROP2 expression (8768 amol / mm2, 75th percentile of breast cancer cohort). HER2 expression below LOQ. Fig. 14C: Case with high HER2 expression (6035 amol / mm2, 98th percentile). Low TROP2 expression (1089 amol / mm2, 14th percentile). Fig. 14D: Case with low / moderate HER2 expression (720 amol / mm2, 78th percentile), and high TROP2 expression (10207 amol / mm2, 85th percentile). Fig. 14E: Case with heterogeneous HER2 and TROP2 expression (964 amol / mm2HER2 and 6924 amol / mm2TROP2).Fig. 15 is a table showing the quantification of HER2 and TROP2 expression in unselected breast cancer cohort of 323 cases, in accordance with some embodiments.Figs. 16A-16B are cell line microarray (CMA) images used in the TROP2 and HER2 standardization, in accordance with some embodiments. Fig. 16A: with CK channel off. Fig. 16B: with CK channel on.Figs. 17A-17B illustrate certain aspects of the HER2 antibody optimization and validation, in accordance with some embodiments. Fig. 17A: Titration of anti-HER2 antibody clone 29D8 with the assay detection system demonstrated 1 ug / mL resulted in the largest signal- to-noise ratio using the breast cancer test array (YTMA 263, 80 tissue cores). Noise and signal were defined as the bottom 15% and top 15% of cores by AQUA score across conditions, respectively. Fig. 17B: HER2 expression (AQUA score) from clone 29D8 correlates strongly with PATHWAY anti-HER2 antibody (clone 4B5).Fig. 18 provides HER2 calibration curves for 6 independent Troplex assay experiments, in accordance with some embodiments.Figs. 19A-19B provide TROP2 calibration curves for several independent Troplex assay experiments, in accordance with some embodiments.Fig. 20 provides a plot of averaged TROP2 normalized response factors for 6 CMAs to determine upper limit of linearity (LOL), in accordance with some embodiments.Fig. 21 provides inter-assay regressions of HER2 and TROP2 across individual TMAs for Figs. 12D-12E.Fig. 22 provides histogram with overlayed density plot of HER2 and TROP2 expression in unselected breast cancer cohort of 323 cases (YTMAs 489 and 499), in accordance with some embodiments.Figs. 23A-23D provides tissue blocks comparison data, in accordance with some embodiments.Fig. 24 provides a schematic diagram of laboratory test development process for Troplex assay optimization and validation, in accordance with some embodiments.Fig. 25 provides a schematic diagram of verification / validation of Troplex assay performance specifications, in accordance with some embodiments.Fig. 26 provides images of CMA625 (cell line microarray 625) stained with anti-HER2 (Clone 29D8) and anti-TROP2 (Clone 2151), DAPI (Blue), CK (Green), HER2 (Red) & TROP2 (Yellow).Fig. 27 illustrates certain aspects of unit conversion of data to attomol / mm2, in accordance with some embodiments.Figs. 28A-28B provides the titration Curves of HER2 (Clone 29D8) and TROP2 primary (Clone 2151) antibodies, in accordance with some embodiments.Figs. 29A-29B provides HER2 and TROP2 standard curves of one CMA625 control, in accordance with some embodiments.Figs. 30A-30B show the QIF images of HER2 standard cell lines (Fig. 30A) and TROP2 standard cell lines (Fig. 3 OB) on CMA625 control. DAPI (Blue), CK (Off), HER2 (Red) & TROP2 (Yellow).Fig. 31 demonstrates the inter-assay reproducibility of HER2 protein measurement in 40 selected BC cases, in accordance with some embodiments. Linear regressions of average amol / mm2values (Left) and average Qymia scores (Right) of HER2 protein quantified by HS- HER2 and Troplex Assays.Figs. 32A-32B illustrate certain aspects of the distribution of HER2 (Fig. 32A) and TROP2 (Fig. 32B) protein in 40 BC cases quantified by Troplex assay, in accordance with some embodiments.Figs. 33A-33B provide the HER2 (Fig. 33A) and Trop2 (Fig. 33B) calibration curves of CMA 625s for LOD and LOQ calculations, in accordance with some embodiments.Figs. 34A-34B provide the linear regressions of HER2 and TROP2 protein in 10 WTS cases by Inter-operator Test, in accordance with some embodiments.Figs. 35A-35B provide tables on calculations of unit conversion for each cell line to attomole / mm2, in accordance with some embodiments.Figs. 36A-36B provide representative QIF images of different HER2 and TROP2 expression patterns in WTSs (Fig. 36A) and heterogeneity of HER2 and TR0P2 in a single core biopsy of BC case (Fig. 36B), in accordance with some embodiments.Fig. 37 provides a table of analytical assessment of HER2 protein in 40 BC cases by the Troplex Assay, in accordance with some embodiments.Fig. 38 provides a table of the quantification summary of HER2 and TROP2 proteins in 40 BC cases by the Troplex Assay, in accordance with some embodiments.Figs. 39-41 show a sample clinal TROPLEX Assay Report, in accordance with some embodiments.Fig. 42 provides a table evaluating the association between HS-HER2 and TNNT, in accordance with some embodiments.Fig. 43 demonstrate that breast cancer patients with higher HER2 level (as measured by percentile) responded better to anti-HER2 ADC treatments (Trastuzumab deruxtecan, TDXd), in accordance with some embodiments.Fig. 44 illustrates certain aspects of the HER2 level distribution in BC cases in the TROPLEX Prospective Study, in accordance with some embodiments.Figs. 45A-45B illustrate certain aspects of the HER2 vs TROP2 measurements in BC cases in the TROPLEX Prospective Study, in accordance with some embodiments.DETAILED DESCRIPTIONThe following disclosure provides many different embodiments, or examples, for implementing different features of the provided subject matter. Specific examples of components and arrangements are described below to simplify the present disclosure. These are, of course, merely examples and are not intended to be limiting. For example, the formation of a first feature over or on a second feature in the description that follows may include embodiments in which the first and second features are formed in direct contact and may also include embodiments in which additional features may be formed between the first and second features, such that the first and second features may not be in direct contact. In addition, the present disclosure may repeat reference numerals and / or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and / or configurations discussed.In some cases, multiple antibody-drug conjugates (ADCs) targeting different cancerspecific antigens are available for the treatment of a single type of cancer. Due to lack of study, safety, governmental agency regulations, and other reasons, these ADCs cannot be used at the same time. Rather, the ADC that is used first is currently dependent on the subjective opinion of the physician, and there is a need for means to provide objective information which can assist the managing physician in ADC drug selection.Furthermore, as more and more antibody-drug conjugate (ADC) therapeutics progress to the clinic, the need of such diagnosis is expected to increase.While not bound by theory, it is proposed that antigen expression levels effect ADC response. Specifically, the more ADC target present the more likely the patient will benefit from the drug. For example, a cancer tissue or cells that highly express a certain cancer-specific antigen is expected to be more susceptible to an ADC that target this antigen specifically, and vice versa. (See e.g., Figs. 3A-3D.) Accordingly, the selection of the most effective ADC requires a quantitative, in vitro companion diagnostic (and / or sets of diagnostics) that measure the level of each ADC target, ideally using minimal amounts of tissue.Furthermore, using breast cancer and two ADCs (one targeting HER2 and one targeting TROP2) as a non-limiting example, an assay that allows clinicians to optimize the selection of the patients-specific ADC therapy was developed. This assay uses antigen level standards constructed from available samples (e.g., cancer samples or cancer cell lines) and then compares antigen levels measured in cancer tissues / cells obtained from patients with the standards to determine the quantitative level of target in amol / mm2which can direct the clinician to the most effect ADC.Accordingly, in some aspects, the present invention is directed to a method of treating a cancer in a subject in need thereof.In some aspects, the present invention is directed to a method for selecting a cancer treatment for a subject in need thereof.In some embodiments, the present invention is directed to a method of predicting an outcome of a treatment of a cancer with a sample from the cancer or a method of performing an in vitro examination on a cancer sample.In some embodiments, the present invention is directed to method of constructing a cancer antigen level standard.DefinitionsAs used herein, each of the following terms has the meaning associated with it in this section. Unless defined otherwise, all technical and scientific terms used herein generally have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Generally, the nomenclature used herein and the laboratory procedures in animal pharmacology, pharmaceutical science, peptide chemistry, organic chemistry and cancer biology are those well-known and commonly employed in the art. It should be understood that the order of steps or order for performing certain actions is immaterial, so long as the present teachings remain operable. Any use of section headings is intended to aid reading of the document and is not to be interpreted as limiting; information that is relevant to a section heading may occur within or outside of that particular section. All publications, patents, and patent documents referred to in this document are incorporated by reference herein in their entirety, as though individually incorporated by reference.In the application, where an element or component is said to be included in and / or selected from a list of recited elements or components, it should be understood that the element or component can be any one of the recited elements or components and can be selected from a group consisting of two or more of the recited elements or components.In the methods described herein, the acts can be carried out in any order, except when a temporal or operational sequence is explicitly recited. Furthermore, specified acts can be carried out concurrently unless explicit claim language recites that they be carried out separately. For example, a claimed act of doing X and a claimed act of doing Y can be conducted simultaneously within a single operation, and the resulting process will fall within the literal scope of the claimed process.In this document, the terms "a," "an," or "the" are used to include one or more than one unless the context clearly dictates otherwise. The term "or" is used to refer to a nonexclusive "or" unless otherwise indicated. The statement "at least one of A and B" or "at least one of A or B" has the same meaning as "A, B, or A and B.""About" as used herein when referring to a measurable value such as an amount, a temporal duration, and the like, is meant to encompass variations of ±20% or ±10%, in certainembodiments ±5%, in certain embodiments ±1%, in certain embodiments ±0.1% from the specified value, as such variations are appropriate to perform the disclosed methods.Abbreviation: HERZ: Human Epidermal Growth Factor Receptor 2; TROP2: Human Trophoblast Cell-surface Antigen 2; CK: Cytokeratins TP: True Positive; TN: True Negative; FOV: Field of view; FP: False Positive; FN: False Negative; IHC: Immunohistochemistry; FISH: Fluorescent in situ hybridization; ATCC: American Type Culture Collection; CMA: Cell Line Microarray; TMA Tissue Microarray; WTS: Whole Tissue Section; ROI: Region of Interest; ADCs: Antibody Drug Conjugates; T-DXd: Trastuzumab Deruxtecan; SG: Sacituzumab Govitecan; QDAP: Quantitative Diagnostics in Anatomy Pathology; LIMS: Laboratory Information Management SystemMethod of Treating CancerIn some aspects, the present invention is directed to a method of treating a cancer in a subject in need thereof.Desirable effects of treating / treatment of cancer include, but are not limited to, alleviating or ameliorating a symptom associated with the cancer; preventing or minimizing proliferation, recurrence, or metastasis of the cancer; remission or improved prognosis; and / or diminishing any direct or indirect pathological consequences of the cancer.In some embodiments, the method comprises obtaining a cancer sample from the subject; determining a first level of a first cancer-specific antigen in the cancer sample; determining a second level of a second cancer-specific antigen in the cancer sample; and administering to the subject a first ADC targeting the first cancer-specific antigen or a second ADC targeting the second cancer-specific antigen.In some embodiments, the cancer sample is a biopsy sample or a sample collected by e.g., a fine needle aspiration.In some embodiments, the method comprises administering the first antibody-drug conjugate (ADC) targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value.In some embodiments, the method comprises administering the first antibody-drug conjugate (ADC) targeting the first cancer-specific antigen if the first level is equal to or higherthan a first predetermined value and the second level is equal to or lower than a second predetermined value.In some embodiments, the method comprises administering the second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value.In some embodiments, the method comprises administering the second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.In some embodiments, the first or third predetermined value is a threshold value at or above which the first or second ADC targeting the specific cancer-specific antigen is likely to be effective.In some embodiments, the second or fourth predetermined value is a threshold value at or below which the first or second ADC targeting the specific cancer-specific antigen is less likely to be effective.In some embodiments, in the case that the first level is equal to or higher than the first predetermined value and the second level is equal to or higher than the third predetermined value, the method comprises administering either one of the first ADC or the second ADC to the subject. Alternatively, the first level is compared with the second level, and the first ADC is administered if the first level is higher and the second ADC is administered if the second level is higher.In some embodiments, in the case that the first level is equal to or lower than the second predetermined level and the second level is equal to or lower than the fourth predetermined level, the first level is compared with the second level. In some embodiments, the first ADC is administered if the first level is higher and the second ADC is administered if the second level is higher.It is worth noting that the number of cancer-specific antigens and ADCs specifically targeting the antigens are not limited to two. In the case that the number of the antigens and ADCs exceeds two, more comparisons with additional threshold values can be performed according to the methods disclosed herein to determine the most effective ADC for a particular cancer patient according to the disclosure herein. In some embodiments, the number is 3, 4, 5, 6,7, 8, 9, 10, or more. In some embodiments, the cases where the cancer-specific antigens and ADCs exceed two are specifically considered part of the present invention.In some embodiments, the first level, the first predetermined value, and / or the third predetermined value are expressed as absolute levels of the first cancer-specific antigen. For example, absolute levels of antigen can be determined using imaging-based methods (such as the quantitative immunofluorescence method herein) and expressed as amount per area, such as amol / mm2.Since the determination of threshold values expressed in terms of absolute values sometimes requires a more extensive study, in some embodiments the threshold values are expressed as percentile rank in a frequency distribution. In some embodiments, percentile rankCF - (0.5 x F) PR - - -x100 can be expressed as N , wherein the cumulative frequency (CF) is the count of all scores less than or equal to the score of interest, F is the frequency for the score of interest, and N is the number of scores in the distribution.In some embodiments, the second level, the second predetermined value, and / or the fourth predetermined value are expressed as absolute levels of the second cancer-specific antigen.In some embodiments, the first level, the first predetermined value, and / or the third predetermined value are expressed as a percentile rank of the levels of the first cancer-specific antigen in a collection of samples of the cancer.In some embodiments, the second level, the second predetermined value, and / or the fourth predetermined value are expressed as a percentile rank of the level of the second cancerspecific antigen in the collection of samples of the cancer.In some embodiments, the first predetermined level and / or the third predetermined level is about 1stpercentile, about 2ndpercentile, about 5thpercentile, about 10thpercentile, about 15thpercentile, about 20thpercentile, about 25thpercentile, about 30thpercentile, about 35thpercentile, about 40thpercentile, about 45thpercentile, about 50thpercentile, about 55thpercentile, about 60thpercentile, about 65thpercentile, about 70thpercentile, about 75thpercentile, or about 80thpercentile, with the lowest expression level being 0thpercentile and the highest expression level being 100thpercentile.In some embodiments, the second predetermined level and / or the fourth predetermined level is about 99thpercentile, about 98thpercentile, about 95thpercentile, about 90thpercentile, about 85thpercentile, about 80thpercentile, about 75thpercentile, about 70thpercentile, about 65thpercentile, about 60thpercentile, about 55thpercentile, about 50thpercentile, about 45thpercentile, about 40thpercentile, about 35thpercentile, about 30thpercentile, about 25thpercentile, or about 20thpercentile, with the lowest expression level being 0thpercentile and the highest expression level being 100thpercentile.In some embodiments, the determination of percentile ranks is based on a frequency distribution of cancer-specific antigen levels in a representative collection of cancer samples, such as a collection of cancer tissues / cells from the same type of cancer of interest, such as a collection cancer tissues / cells from patients suffering from cancers of the same type, stage, aggressiveness, or the like.In some embodiments, the collection of samples comprises biopsy samples and / or primary cancer cells derived from patients of the cancer, and or cancer cell lines.In some embodiments, the first level and / or the second level is determined by a quantitative immunofluorescence method. In some embodiments, the quantitative immunofluorescence method is a multiplex method that determines the first level and the second level in the same immunostaining assay. Quantitative immunofluorescence methods, such as multiplex methods of the same, are described in, for example, Harms et al. (Mod Pathol. 2023 Jul;36(7):100197), Yaghoobi et al. (Expert Rev Mol Diagn. 2020 May;20(5):509-522), MacNeil et al. (Biotechniques. 2020 Dec;69(6):460-468). In some embodiments, the first level and / or the second level is determined by a quantitative chromogenic method. Quantitative chromogenic methods are described in, for example, Gaule et al. (JAMA Oncol. 2017 Feb l;3(2):256-259), Morilla et al. Lab Invest. 2020 Jan;100(l):4-15).In some embodiments, the first level and / or the second level is determined by the quantitative immunofluorescence method and / or the quantitative chromogenic method according to an established relationship between an imaging signal strength of the cancer specific antigen and a known level of the cancer specific antigen. In some embodiments, the established relationship between the immunofluorescence signal strength and the known level allows the conversion of immunofluorescence signal strength to concentration (such as attomoles), such as immunofluorescence signal strength per area (such as per mm2, per pixel, etc.) to concentrationper area (such as per mm2, per pixel, etc.). In some embodiments, a cell line with known antigen concentrations is used as standards to establish such a relationship. In some embodiments, a gel standard with known concentrations of the antigens is used as a standard to establish such relationship.In some embodiments, the converted absolute concentration is in turn converted to a percentile rank based on an established standard of absolute level / percentile rank relationship.The type of cancers that are treatable by the method disclosed herein is not limited. There are multiple cancer types which are treatable by more than one ADC. Currently, there are already more than three hundred ADCs being tested in clinical trials for treating various cancers, and many cancer types are being targeted in more than one cancer specific antigen. This is even for some clinically approved ADCs. For example, both polatuzumab vedotin-piiq (targeting CD79) and loncastuximab tesirine-lpyl (targeting CD 19) have been approved to be used for large B-cell lymphoma; and trastuzumab emtansine (targeting HER2), trastuzumab deruxtecan (targeting HER2) and sacituzumab govitecan (targeting Trop2) have been approved to be used for breast cancer. In some embodiments, the cancer is breast cancer or large B-cell lymphoma.In some embodiments, the first cancer-specific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancer-specific antigen is tumor associated calcium signal transducer 2 (TROP2).In some embodiments, the first cancer-specific antigen is CD19, and / or the second cancer-specific antigen is CD79.In some embodiments, the subject is a human.Method of Selecting Cancer TreatmentIn some aspects, the present invention is directed to a method for selecting a cancer treatment for a subject in need thereof.In some embodiments, the cancer is treatable by two or more antibody drug conjugates (ADCs), which comprises a first ADC targeting the first cancer-specific antigen, and a second ADC targeting the second cancer-specific antigen.In some embodiments, the method comprises: obtaining a cancer sample from the subject; determining a first level of a first cancer-specific antigen in the sample; determining a second level of a second cancer-specific antigen in the sample.In some embodiments, the method further comprises making a prediction that: the cancer is more susceptible to a first ADC targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value and the second level is equal to or lower than a second predetermined value.In some embodiments, the method further comprises making a prediction that the cancer is more susceptible to a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.In some embodiments, the cancer, the antigens, the ADCs, the antigen levels (such as the absolute antigen levels or the antigen percentiles), the predetermined levels, and so on are the same as or similar to those as disclosed elsewhere herein, such as in the “Method of Treating Cancer” section.Method of Predicting Outcome of Treatment of CancerIn some aspects, the present invention is directed to a method of predicting an outcome of a treatment of a cancer with a sample from the cancer.In some embodiments, the cancer is treatable by two or more antibody drug conjugates (ADCs), which comprises a first ADC targeting the first cancer-specific antigen, and a second ADC targeting the second cancer-specific antigen.In some embodiments, the method comprises: determining a first level of a first cancerspecific antigen in the sample; and / or determining a second level of a second cancer-specific antigen in the sample.In some embodiments, the method further comprises making a prediction that: the cancer is more susceptible to the first ADC targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value and the second level is equal to or lower than a second predetermined value.In some embodiments, the method further comprises making a prediction that the cancer is more susceptible to a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.In some embodiments, the cancer, the cancer sample, the antigens, the ADCs, the antigen levels (such as the absolute antigen levels or the antigen percentiles), the predetermined levels, and so on are the same as or similar to those as disclosed elsewhere herein, such as in the “Method of Treating Cancer” section.Method of Performing in vitro Examination on Cancer SampleIn some aspects, the present invention is directed to a method of performing an in vitro examination on a cancer sample.In some embodiments, the cancer is treatable by two or more antibody drug conjugates (ADCs), which comprises a first ADC targeting the first cancer-specific antigen, and a second ADC targeting the second cancer-specific antigen.In some embodiments, the method comprises: determining a first level of a first cancerspecific antigen in the sample; and / or determining a second level of a second cancer-specific antigen in the sample.In some embodiments, the method further comprises making a prediction that: the cancer is more susceptible to a first ADC targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value and the second level is equal to or lower than a second predetermined value.In some embodiments, the method further comprises making a prediction that the cancer is more susceptible to a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.In some embodiments, the cancer, the antigens, the ADCs, the antigen levels (such as the absolute antigen levels or the antigen percentiles), the predetermined levels, and so on are the same as or similar to those as disclosed elsewhere herein, such as in the “Method of Treating Cancer” section.Method of Constructing Cancer Antigen Level StandardIn some aspects, the present study is directed to a method of constructing a cancer antigen level standard for a cancer type.In some embodiments, the cancer antigen level standard comprises frequency distributions of two or more cancer-specific antigen levels in cancer tissues or cancer cells, such as cancer tissues or cancer cells obtained from and / or representative of a group of cancer patients.In some embodiments, cancer antigen level standard is useful for the methods described elsewhere, such as when determining the percentile rank of cancer-specific antigen level in a cancer sample.In some embodiments, the cancer patients all suffer from a cancer of the same type. In some embodiments, the cancer patients all suffer from a cancer of the same type, stage, and / or aggressiveness.In some embodiments, the method comprises: determining the levels of a first cancerspecific antigen in a collection of cancer samples of the cancer type; plotting a frequency distribution of the first cancer-specific antigen levels such that each given level of the first cancer-specific antigen corresponds to a percentile rank of the first cancer-specific antigen levels (such as in a cancer-specific disease population); determining the levels of a second cancerspecific antigen in the collection of cancer samples; plotting a frequency distribution of the second cancer-specific antigen levels such that each given level of the second cancer-specific antigen corresponds to a percentile rank of the second cancer-specific antigen levels. In the case that there are more than two cancer-specific antigens, the above steps can be repeated for the rest of the cancer-specific antigens.In some embodiments, the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.In some embodiments, the levels of the first cancer-specific antigen and / or the levels of the second cancer-specific antigen are determined by a quantitative immunofluorescence method or a quantitative chromogenic method.In some embodiments, the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines a first level of the first cancerspecific antigen and a second level of the second cancer-specific antigen of a given sample in the collection of cancer samples in a same immunostaining assay.In some embodiments, the method further comprises establishing a relationship between immunofluorescence signal strength of a cancer specific antigen and an absolute level of thecancer specific antigen. In some embodiments, the established relationship between the immunofluorescence signal strength and the absolute level allows the conversion of immunofluorescence signal strength to concentration (such as attomoles), such as immunofluorescence signal strength per area (such as per mm2, per pixel, etc.) to concentration per area (such as per mm2, per pixel, etc.).In some embodiments, a cell line with known antigen concentrations is used as standards to establish such a relationship. In some embodiments, a gel standard with known concentrations of the antigens is used as a standard to establish such relationship.In some embodiments, the cancer, the antigens, the antigen levels, and so on are the same as or similar to those as disclosed elsewhere herein, such as in the “Method of Treating Cancer” section.ExamplesThe instant specification further describes in detail by reference to the following experimental examples. These examples are provided for purposes of illustration only, and are not intended to be limiting unless so specified. Thus, the instant specification should in no way be construed as being limited to the following examples, but rather, should be construed to encompass any and all variations which become evident as a result of the teaching provided herein.Example 1The study described herein (“the present study”) developed a multiplex assay with quantitative, standardized assessment of two or more ADC targets where the assay is accompanied by a series of quantitative controls based on a concept referred to as “ADCelecf ’ herein. The controls allow creation of a standard curve, assessed in attomoles / mm2of protein on a histology slide. Using this calibrated standard, the assay determines the level of the ADC target in a quantitative, reproducible manner.Each of the ADC target level can then be compared to levels of the target seen in a population of patients with similar disease states or to the absolute levels of the protein required to benefit from the ADC of interest.Notably, even without the knowledge of the threshold in terms of absolute levels, the relative levels in a population of patients with similar disease states can allow the clinician to select the ADC that has the highest percentile in the population that will increase the likelihood of benefit from the therapy.Following the ADCelect concept conceived in this study, a HER2, TR0P2, and cytokeratin (CK) multiplex immunofluorescence assay was constructed with a DAPI nuclear counterstain using clinical-grade laboratory equipment for automated slide staining and scanning. The present study assessed the diagnostic assay performance and expression characteristics of HER2 and TROP2 in the retrospective breast cancer tissue cohorts and demonstrated that many patients are relatively higher for one target or the other. This assay was standardized for individual patient specimens using cell lines with mass-spectrometry defined levels of each target (in amol / mm2). This demonstrated a proof-of-concept and a workflow / method to create an ADC selector assay that can be taken to the clinic to aid in determining which ADC a patient should receive based on the relative levels of expression of each ADC target.The present study examined the choice between T-DXd and SG which are both approved for metastatic breast cancer. Studies have shown benefit from both drugs, but no comparative studies or assays have yet been examined. Using the multiplex quantitative assay on Yale breast cancer cohort containing over 300 patients, the present study discovered that about 35% of cases express high levels of one target, but not the other. Thus, the assay developed herein is able to assist the oncologist in therapeutic selection of the most promising ADCs for at least 70% of patients and probably more.Example 2: Quantitative Multiplex Immunofluorescence Assay for Trop2 and Her2 Expression in Breast Cancer: Towards Guiding Patient Selection for Antibody Drug Conjugate TherapiesEmerging antibody drug conjugate (ADC) therapies targeting human trophoblast cellsurface antigen (Trop2) and human epidermal growth factor receptor 2 (Her2) are transforming the treatment landscape for breast cancer. Sacituzumab govitecan (SG) and trastuzumab deruxtecan (T-DXd) have gained approval for an overlapping set of "Her2-low" metastatic breast cancers, including hormone receptor (HR)-positive Her2 non-amplified and "triple-negative"subtypes. Nevertheless, the optimal selection of patients and treatment sequencing for these ADC therapies remains a clinical challenge. Clinical trial objective response rates to SG are approximately 30%, compared to 30-90% for T-DXd depending on Her2 expression levels. While both drugs are thought to be targeted therapies, the value of measuring the target and the best methods to do so are still not established. It was believed that quantitative measurement of Trop2 and Her2 antigen expression levels could establish thresholds for responders, enabling more effective patient selection for ADC therapies. Here, the present study presents a Trop2, high-sensitivity Her2, and cytokeratin (CK) quantitative immunofluorescence (QIF) multiplex assay. Using a ten-cell line standard array and proteomic mass spectrometry, the present study was able to convert tumor compartment QIF intensity to protein concentration in amol / mm2for tissue specimens. Anti-Her2, anti-Trop2 antibodies, and fluorescence detection systems were titrated and combined to maximize signal-to-noise ratio on the cell line standard array and breast cancer tissue microarrays (TMA). The multiplex assay was designed for automated slide Stainers (Leica BOND Rx) and fluorescence slide scanning (Rarecyte CyteFinder II HT). The present study performed the analyses in QuPath using an image processing plugin developed for automated QIF / IHC analysis (Qymia). Reproducible Trop2 and Her2 QIF scoring (R2> 0.95) was achieved across multiple staining batches using serial sections of breast cancer TMAs and cell standard arrays. This assay has a Trop2 linear range between 220.3 - 10614 amol / mm2(about 1 million Trop2 receptors / cell) and Her2 linear range between 70 - 3329 amol / mm2(about 200,000 Her2 receptors / cell). The present study then applied this multiplex assay to two serial retrospective primary breast cancer cohorts from Yale University to quantitatively measure Trop2 and Her2 expression (338 clinical cases). The present study found a weak negative correlation between Trop2 and Her2 expression in the breast cancer cohorts (Pearson r = -0.14, p = 0.0097, n = 338). Trop2 expression levels were above the limit of detection (LOD) in 95.56% of cases, with 14.2% exceeding the limit of linearity (LOL). For Her2, 75. 15% of cases were above the LOD, with 6.8% exceeding the LOL. Both Trop2 and Her2 were below the LOD in 1.48% of cases, which was defined as “negative.” The present study found 23.37% expressed Trop2 and were Her2-negative, and 2.96% expressed Her2 and were Trop2-negative.Table 1 : Summary of Her2 and Trop2 protein expression levels in serial retrospective primary breast cancer cohort of 338 cases using the high-sensitivity Her2 and Trop2 immunofluorescent multiplex assay.Table 1.Hi: above LOL, Q: within linear range, Neg: below LODExample 3: Quantitative Multiplex Immunofluorescence Assay for TROP2 and HER2 Expression in Breast Cancer: Towards Guiding Patient Selection for Antibody Drug Conjugate TherapiesAccurate quantification of HER2 and trophoblast cell-surface antigen 2 (TROP2) expression could aid in identifying cancer patients likely to benefit from emerging HER2 and TROP2 antibody-drug conjugate (ADC) therapies or potentially help oncologist choose which drug to use first on the basis of the level of the ADC target in the tumor. The present study developed a multiplex quantitative immunofluorescence (QIF) assay to simultaneously measureHER2 and TR0P2 protein levels in cancer tissue. To measure the levels of target, the present study created Qymia, an open-source QuPath extension enabling molecular compartmentalization and quantification of immunofluorescencein the same assay as a cell line standard with known levels of target.. Optimal antibody clones and concentrations were determined by staining TMAs to maximize si nal-to-noise ratios. Cell line microarrays with mass spectrometry-quantified HER2 / TROP2 abundances generated calibration curves to convert QIF signal into absolute protein levels (attomoles / mm2). The multiplex assay demonstrated linearity across a wide dynamic range of biomarker expression with strong inter-assay / inter- operator reproducibility. Application of this assay to a serial collection of 323 breast cancer cases in a TMA revealed a weak inverse correlation existed between HER2 and TR0P2 (r=-0.17, p=0.001). HER2 was quantifiable in 50.5% of cases, including 17% of triple-negative breast cancers. TROP2 was quantifiable in 92.6% of cases across all subtypes. 47.1% of cases expressed TROP2 and were HER2-negative, and 4.95% expressed HER2 and were TROP2- negative. This multiplex immunofluorescence assay provides an approach to precisely measure HER2 / TROP2 levels within breast cancer tissue and compare relative levels of each as a function of the levels in a breast cancer tissue population. This approach can help identify patients that benefit from emerging targeted ADC therapies based on their individualized target expression profile.Example 3a:Human epidermal growth factor receptor 2 (HER2) and trophoblast cell-surface antigen 2 (TROP2) are important therapeutic targets in breast cancer. HER2 overexpression resulting from ERBB2 gene amplification occurs in approximately 15-20% of breast cancers and can be targeted by anti-HER2 regimens using trastuzumab and / or pertuzumab. More recently, clinical trials for the HER2 targeting antibody-drug conjugate (ADC) trastuzumab deruxtecan (T-DXdT-DXd) has led to striking results in clinical activity towards both ERBB2 gene amplified and immunohistochemistry (IHC) “HER2-low” breast cancers. Strikingly, T-DXdT-DXd has demonstrated objective response rates (ORR) of up to 50% in patients with estrogen-receptor (ER)-positive and ER-negative metastatic breast cancer. In tumors expressing HER2 scored IHC 1+ or 2+, has doubled progression-free survival (PFS) and improved overall survival (OS) compared to standard chemotherapies.TR0P2 is an emerging therapeutic target expressed across the spectrum of breast cancer. The TROP2-targeted ADC sacituzumab govitecan (SG) recently received FDA approval for patients with unresectable locally advanced or metastatic hormone receptor-positive breast cancer as well as received accelerated approval for metastatic triple negative breast cancer also due to its impressive clinical efficacy in recent trials (TROPiCs and ASCENT). These approvals were all granted without a companion diagnostic test to assess TR0P2 expression levels. TR0P2 is also the target of several other ADC including datopotamab deruxtecan, sacituzumab tirumotecan, and others in various stages of evaluation.While the ADC class of drugs has shown great promise, they are not free from adverse reactions, including neutropenia, nausea, anemia, and occasionally severe adverse reactions including interstitial lung disease (10-12% for T-DXd) or febrile neutropenia (6-8% for SG). Furthermore, currently both drugs have approval in the same setting in advanced breast cancer. Thus, there is clinical justification for a tool that can select the best drug for each patient based on the level of ADC target or other biologically relevant information.Accurate measurement of both HER2 and TROP2 levels is likely to be critical for identifying patients who may benefit from these targeted ADC therapies. For HER2, current clinical assays using IHC and in situ hybridization (ISH) are optimized to dichotomize HER2 status as simply positive or negative based on ERBB2 amplification, lacking sensitivity in the low expression range. Though there is not yet a companion diagnostic test that measures TROP2 expression for TROP2- ADC therapy, the TROPiCs-02 trial for SG demonstrated that PFS is significantly correlated with TROP2 levels read by IHC (but not OS). While not always emphasized in the published literature and conference presentations of studies using T-DXd and SG, there are clear correlations between target expression and PFS / ORR when semi- quantitatively assessed by IHC scoring. This data suggests that sensitive and reproducible measurement of ADC target expression may help identify patients that will respond to these therapies through the development of new, more precise diagnostic assays.Quantitative immunofluorescence offers a promising alternative for sensitive protein detection, with multiplex potential across a wide dynamic range. Here, the present study sought to develop a high-sensitivity quantitative multiplex immunofluorescence assay to simultaneously measure both HER2 and TROP2 protein expression in breast cancer tissues. Optimizing this assay required: 1) identifying optimal antibody clones and dilutions, 2) generating cell line-basedstandard curves for protein quantification, and 3) validating multiplex staining performance against standard singleplex assays. The present study applied this assay to quantify HER2 and TR0P2 levels across breast cancer cases to explore heterogeneity in expression and the relationship of the two targets to each other. In the future, this multiplex protein assay could help guide in the optimal selection of patients for treatment with HER2- and TR0P2-ADCs.Example 3b: Materials and MethodsCell lines tissue cultureA set of cell lines were obtained from American Type Culture Collection (ATCC, Manassas, VA 20110, USA) including: JURKAT TIB-152, BT-20 HTB-19, T47D #HTB-133, ZR-75-1 #CRL-1500, BT-483 #HTB-121 , TT #CRL-1803, VCaP CRL-2876, CAL-27 #CRL- 2095, MDA-MB-468 # HTB-132, DLD-1 CCL-221, A431 CRL-1555 . Each cell line was cultured in accordance with the culture method provided by ATCC. Cells harvested at the end of log phase were pelleted, frozen and shipped to Protypia (now Inotiv) for measurement of the expression of HER2 and TROP2 in attomols (amol) / pg of total protein.Liquid chromatography-tandem mass spectrometry (LC-MS / MS)Protein abundance of HERZ and TROP2 in the cell lines was analyzed by LC-MS / MS at Protypia, Inc, Nashville, TN, USA. Protein was extracted from frozen cell pellets with the M- PERTM reagent (ThermoFisher Scientific, Rockford, IL) supplemented with HALTTM protease inhibitor cocktail (ThermoFisher Scientific) according to the manufacturer's directions. Protein content was analyzed with the BCA reagent (ThermoFisher Scientific) and 100 pg protein was reduced, alkylated, and digested with trypsin. Standards of the HER2 peptides ([13C6,15N4-Arg]- DPPFCVAR (SEQ ID NO: 1) and [13C6,15N4-Arg] -ELVSEFSR (SEQ ID NO:2)) and TROP2 peptides ([13Ce,13N4-Arg]-GESLFQGR, SEQ ID NO:3) (99.5% isotopic purity; Vivitide, Gardner, MA) were added to the tryptic digest, which was fractionated by high pH reverse phase chromatography with disposable spin columns (ThermoFisher Scientific). Fractions containing the target peptides were analyzed by LC-MS / MS parallel reaction monitoring. MS / MS transitions for the labeled standard peptides and the unlabeled HER2 peptides from the samples were analyzed with Skyline and HER2 protein abundances were calculated as amol / pg proteinfrom the ratio of summed signals for the three most intense MS / MS transitions for the sequences and the added standard amounts.HER2 and TR0P2 calibration CMAThe HER2 and TR0P2 calibration cell microarray (CMA) was built by Array Science LLC (Sausalito, CA). Cell lines were arranged by the map shown in Figs. 16A-16B with twofold redundancy. Only selected cell lines from this array that were within the linear range of response were used for the final calibration curves. Mass spectrometry results from intracellular HER2 peptide (ELVSEFSR, SEQ ID NO:2) and extracellular TROP2 peptide (GESLFQGR, SEQ ID NO:3) are used for estimates of protein abundances for cell line standards.HER2 Standardization Yale TMA (YTMA263), Breast Cancer Cohorts (YTMA489, YTMA499) and TNBC (YTMA311) cohortsThe breast cancer test array (YTMA263) used throughout this study is a HER2 standardization tissue microarray (TMA) that was built by extracting 0.6 mm cores from 80 selected FFPE breast carcinomas seen at Yale Pathology between 1998 and 2011, 10 breast cell lines controls (prepared at Yale), and 10 non-tumor breast tissue cores. Cases were arranged in columns according to their HER2 status. Retrospective breast cancer cohort arrays (YTMA489 and YTMA499) were built from 263 and 190 FFPE serial breast carcinomas seen at Yale Pathology between 2011-2012 and 2013-2014. The TNBC cohort array (YTMA311) was built from serially collected tissue blocks from 139 patients diagnosed between 1962 and 2006. Further details on clinicopathologic characteristics collected from the cohorts used for TMA construction can be found within the respective references.Quantitative immunofluorescence staining (QIF)For “singleplex” quantitative immunofluorescence (QIF) staining, the present study quantifies a single target biomarker (HER2 or TROP2) inside the epithelial molecular compartment defined by cytokeratin (CK) expression with a protocol to stain target antigen, pan- CK, and DAPI. For the “multiplex” or “Troplex” staining referred to in this manuscript, the protocol was modified to stain HER2, TROP2, pan-CK, and DAPI. QIF staining was performed on the Leica BOND Rx auto-staining platform using designated reagents and the followingstaining protocol. Wash steps with BOND wash solution (AR9590) were used between incubations but excluded from following description. TMA / CMA sections were baked in 60 °C incubator for 1 hour prior to staining. Slides were deparaffinized with BOND dewax solution (AR9222) and subjected to antigen retrieval with pH 9.0 BOND epitope retrieval solution 2 (AR9640) at 97 °C for 20 minutes. Next, slides were incubated with ReadyProbes Endogenous HRP and AP blocking solution (Invitrogen, R37629) for 10 minutes. If biotin-tyramide detection was used, blocking of endogenous biotin was performed using an avidin / biotin blocking solutions for 15 minutes each (Abeam, ab64212). Slides were incubated for 30 minutes with 0.3% bovine serum albumin and 0.05% Tween-20 prior to primary antibody incubation. Subsequent steps differed based on staining for singleplex or multiplex assay experiments.For the remaining protocol steps of singleplex staining experiments, HER2 antibodies (29D8, CST #2165 , R-IgG, 1 pg / mL; 4B5, Roche_#107918, R-IgG, prediluted) or TROP2 antibodies (2151, ab238015, M-IgG2b, 0.1 pg / mL; SP295, ab22769, R-IgG, 1 pg / mL; EPR20043, ab214488, R-IgG, 0.1 pg / mL) were then incubated for 60 minutes at room temperature. Several concentrations of antibodies were tested in experiments to determine optimal concentration according to signal -to-noise ratios of the bottom 15% and top 15% of cores in breast cancer test array (example is anti-TROP2 clone 2151 in Fig. 11A and anti-HER2 clone 29D8 in Fig. 17A). For primary antibodies with rabbit IgG isotype, secondary anti-rabbit EnVision+ / HRP polymer (Dako, K400311-2) was incubated for 60 minutes. Correspondingly, primary antibodies with mouse immunoglobulin isotypes were incubated with secondary antimouse EnVision+ / HRP polymer (Dako, K400111-2) for 60 minutes. To visualize HER2 expression, Tyramide signal amplification (TSA) Cyanine 5 (1 :50, Akoya Biosciences, SAT705A001EA). For TROP2 detection, TSA Biotin (1 :50, Akoya Biosciences, SAT700001EA) combined with 60-minute incubation with streptavidin-Alexa Fluor 750 conjugate (20 pg / mL, Invitrogen, S21384) was used. Pan cytokeratin monoclonal antibody (AE1 / AE3) directly conjugated to Alexa Fluor 488 (5 pg / mL, Invitrogen, 53-9003-82) is applied for 60 minutes (combined with streptavidin-Alexa Fluor 750 for TROP2 staining). 4', 6- diamidino-2-phenylindole (DAPI) was used to stain nuclei, and the slides were mounted with ProLong Gold Antifade reagent (Invitrogen, P36930).For multiplex HER2 and TROP2 assays, the optimal concentrations of primary antibodies anti-HER2 clone 29D8 (R-IgG) and anti-TROP2 clone 2151 (M-IgG2b) are combined andincubated for 60 minutes. Secondary anti-rabbit EnVision+ / HRP polymer followed by TSA Cy5 detection steps described above are performed. Next, two washes of a solution containing lOOmM benzoic hydrazide and 50mM H2O2 in phosphate buffered saline are applied for 7 minutes each to eliminate residual horseradish peroxidase activity. Then, secondary anti-mouse EnVision+ / HRP polymer followed by TSA biotin detection steps above are performed. A mixture of pan-CK and streptavidin- Alexa Fluor 750 at concentrations described above are incubated for 60 minutes. The multiplex slides are counterstained with DAPI and mounted with ProLong Gold Antifade reagent.Image acquisition, Qymia, image analysis, and data analysisFluorescent imaging was performed using the Rarecyte Cytefinder II HT (Rarecyte, Seattle, WA, USA), an automated widefield fluorescence slide scanner. Slides were scanned at a magnification of 20x with fixed exposure times and specific filter sets for each fluorophore used (e.g. DAPI, Alexa Fluor 488, Cy5, and Alexa Fluor 750). After fluorescent slide scanning, the present study performed digital image analysis in QuPath using an extension developed and named Qymia (Quantitative Immunofluorescence and Immunohistochemistry Molecular Image Analysis). Qymia employs the same principles as previous software for quantifying tissue immunohistochemical biomarkers via molecular compartmentalization (AQUA). The present study developed Qymia in the lab and will release it upon publication of this work as an open- source extension in QuPath to perform these analyses. All acquired TMA spots were visually assessed and cases with staining artifacts or less than 2% tumor (pan-CK staining) were omitted from the analysis. Cross-sectional area for cell lines were estimated by Cellpose cell segmentation on IHC stained CMAs using the extension for QuPath. Calculations converting mass spectrometry amol / total protein (ug) results to amol / cell area (mm2) were performed. Data analysis was performed in Python with common scientific computing and visualization libraries including NumPy, SciPy, pandas, matplotlib, seaborn and statannotations.Calculation of Limits of Detection, Quantification, and LinearityFollowing the FDA Guidance for Industry Q2(R1) Validation of Analytic Procedures, the present study determined the limit of detection (LOD) and limit of quantification (LOQ) for HER2 and TROP2 biomarkers using Qymia scores of CMA spots and the measured analyteconcentration (amol / mm2) which were obtained by LC-MS / MS. Although a larger range of immunofluorescence response could be modeled by a logistic curve fit (similar to plate-based immunoassays), the precision of measurements using cell line standard arrays is poor outside of the assay’s linear range. For a first calibration standard curve, it was decided to limit standards within the linear range of the assays and utilize linear calibration fits. The calibration curve fit for HER2 and TR0P2 on each array was determined by linear regression after background subtraction of the negative control cell line. Eq. (1) describes the relationship to determine LOD for a linear fit from Q2(R1):where G is the standard deviation of the Qymia score for the negative control and S is the slope of the calibration curve for the array. For the Troplex assay, the present study used 6 CMA slides to calculate analytic limits with a 2-fold redundancy of cell lines per array. The standard deviation for the Qymia score of the negative control (TT) cell line was calculated across arrays and each linear fit was used to calculate 6 LODs, which are presented as a mean with 95% confidence interval (Fig. 15).The LOQ calculation is performed similarly using Eq. (2).To determine the limit of linearity (LOL), the present study plot normalized response factors for each biomarker as described by Huber31. The normalized response factor is the ratio of background subtracted Qymia score (response) to abundance (amol / mm2), divided by the slope of the calibration curve fit. The greater analyte concentration where the normalized response factor plot intersects with lines y = 1.05 or y = 0.95 would be defined as the upper LOL (plotted in Fig. 20). Mentions of LOL in this paper will specifically refer to the upper LOL.Fig. 15 contains the LOD / LOQ / LOL values for the final multiplex HER2 and TROP2 immunofluorescence assay.Example 3c: ResultsThis study establishes a quantitative multiplex immunofluorescence workflow to generate standardized protein abundance measurements for HER2 and TROP2 in breast cancer modeledafter the previous singleplex high sensitivity HER2 assay. The schematic for the assay construction and envisioned report is shown in Fig. 10. The present study quantified area normalized immunofluorescence signal within the tumor epithelial compartment (defined by pan-cytokeratin) using Qymia, a QuPath extension for molecular compartmentalization quantification of whole tissue sections and tissue microarrays (TMAs) developed for this work. Additionally, the present study developed a cell-line microarray where HERZ and TROP2 expression were quantified by mass spectrometry (detailed in subsequent section and methods). This CMA of quantified HER2 and TROP2 protein levels act as standard curves for each immunofluorescence staining batch, allowing for the conversion of immunofluorescence signal into absolute protein abundance in attomoles / mm2. Applying this assay and the Qymia image analysis pipeline to breast cancer tissue microarrays allowed sensitive quantification of HER2 and TROP2 expression across hundreds of cases. The present study then derived percentile scores for each tumor by ranking its HER2 and TROP2 abundance against the retrospective cohort distribution. These percentile scores offer an intuitive scale for oncologists and patients to understand a given tumor’s relative degree of HER2 / TROP2 expression. In the future, correlation of these scores with outcomes after treatment with HER2 and TROP2 targeted therapies, like T-DXd and SG, could help refine thresholds for precise patient selection.Example 3d: Optimization of Sensitivity and Specificity of TROP2 Antibody ImmunofluorescenceOptimization experiments were performed to determine multiplex compatible antibody clones and their optimal effective concentration for each protein target. The present study found a multiplex compatible mouse IgG2b anti-TROP2 antibody clone 2151 that demonstrated high affinity and specificity by signal-to-noise analysis in the breast cancer tissue test TMA. For this TROP2 antibody (2151), the highest signal-to-noise ratio (30.8 ± 3.6) was at an effective concentration of 0.1 pg / mL. The average and standard deviations for the signal-to-noise estimates of singleplex staining experiments with two replicates for each condition are shown in Fig. 11A.The present study found that singleplex staining of the breast cancer test TMA with the optimal concentration of clone 2151 demonstrated highly correlated linear regressions with singleplex staining by two other rabbit anti-TROP2 antibody clones, EPR20043 (R2= 0.829) andSP295 (R2= 0.886) used in the exploratory settings in SG trials (REF)., Each clone recognizes a distinct TROP2 extracellular epitope (Figs. 1 IB-11C). This reinforces that clone 2151 provides a high level of signal-to-noise and target specificity for TROP2. For HER2 detection, the present study used clone 29D8 with conditions established by optimization experiments Moutafi et al. (Lab Invest. 2022; 102(10): 1101-1108) and validated against clone 4B5 (Figs. 11A-11B).Quantitative measurement of TROP2 and HER2 levels in cell linesAs described above, standard arrays were produced from cell pellets derived from a cell lines (including BT-20, T-47D, ZR-75-1, BT-483, TT, VCaP, and CAL-27)(Figs. 16A-16B). LC-MS / MS assays to measure TROP2 extracellular (GESLFQGR, 232-239, SEQ ID NO:3) and HER2 extracellular (DPPFCVAR, 592-599, SEQ ID NO: 1) and intracellular (ELVSEFSR, 126- 133, SEQ ID NO:2) peptides were performed by Protypia / Inotiv described here and in Moutafi et al. (Lab Invest. 2022;102(10): 1101-1108). Protein abundance in amol / cell is converted to amol / area occupied by cells on the slide using QuPath to estimate the area in mm2per cell for each cell line described in Moutafi et al (Lab Invest. 2022; 102(10): 1101-1108). An example of the cell line calibration curve is displayed in Figs. 1 ID and 1 IE, where Fig. 1 IE is the subset of five cell line standards within the linear range of the assay. Replicates of standard curves used for calculation of analytical limits of the multiplex TROP2 and HER2 assay are displayed in Figs. 18, 19A and 19B.Creation of Troplex Assay, Comparison to Singleplex Assays, Inter-assay, and Inter-operator ComparisonThe present study validated the multiplex HER2 & TROP2 assay (Troplex) by comparing it to singleplex assays detecting either HER2 or TROP2 individually (overview TMA QIF images displayed in Fig. 12A). High correlations by linear regressions were observed between the multiplex and singleplex assays for both HER2 (R2= 0.971) (Fig. 12B) and TROP2 (R2= 0.861) (Fig. 12C), indicating that the antibodies do not interfere with each other in the multiplex format. The present study also showed that the additional multiplex reagents do not significantly increase the background for either of the fluorescent channels compared to the singleplex.Additionally, the present study performed inter-assay and inter-operator validation of results in this study. The present study demonstrates strong linear regressions across multipleruns of HER2 and TR0P2 expression results in 386 cores from retrospective breast cancer cohorts and breast cancer test arrays stained by the Troplex assay (Figs. 12D and 12E). Regression results across runs of the multiplex assay for each individual TMA of the cohort are displayed in Fig. 21. The present study also observed high correlations by linear regressions of HER2 and TR0P2 expression across multiple operators (Figs. 12F and 12G).HER2 and TR0P2 Expression Levels in Breast Cancer CohortThe present study used the Troplex assay to measure HER2 and TR0P2 levels in unselected, serial breast cancer cases in tissue microarray (TMA) format with two-fold redundancy. 323 cores with adequate tumor content were shared across the two staining batches. An ordered bar plot of the average value of two cores per patient is shown alongside the calculated LOQ and LOL (Fig. 12A-13E). HER2 expression displayed a skewed distribution (Fig. 22), with most cases showing very low or low expression and a subset displaying HER2 overexpression (Fig. 13A) similar to that reported in Moutafi et al. (Lab Invest.2022; 102(10): 1101-1108). In contrast, TROP2 expression was more continuously distributed (Fig. 13B).The present study found a weak negative correlation between TROP2 and HER2 expression in the breast cancer cohorts (Pearson r = -0.17, p = 0.0014, n = 323) (Fig. 13C). The present study tabulated the results of quantifying HER2 and TROP2 expression for the 323 cases of the breast cancer cohorts in Fig. 15. TROP2 expression levels were above the limit of detection (LOQ) in 96.6% of cases, with 16.7% exceeding the limit of linearity (LOL). For HER2, 84.2% of cases were above the LOQ, with 7.1% exceeding the LOL. 7.4% of cases were below TROP2 LOQ and 49.5% were below HER2 LOQ. Roughly 3% of the cases had both TROP2 and HER2 below the LOQs (TROP2-negative and HER2-negative). 47.1% expressed TROP2 and were HER2-negative, and 4.95% expressed HER2 and were TROP2-negative.The present study quantitatively reports measurements of both HER2 and TROP2 expression across clinical breast cancer receptor subtypes. The present study enriched the retrospective breast cancer cohort arrays using staining results from a TNBC array so that the present study could increase the sample size of representative TNBC cases (from n=39 to n=125 TNBC cases). Figs. 13D and 13E are plots the HER2 and TROP2 expression by clinical breast cancer receptor status of hormone receptors (estrogen or progesterone receptors) and HER2assessment. As expected, the average HER2 expression measured by the quantitative multiplex assay is significantly different across each clinical receptor status group, with clinical HER2- positive cases having the greatest HER2 expression on average that exceeds the LOL (Fig. 13D). However, roughly 17% of TNBC cases have quantifiable levels of HER2 expression (above LOQ). Strikingly, there are several clinically HER2 positive cases that are below the LOQ and have undetectable levels of HER2 expression by the assay. Although, this could be due to limitations in sampling the tumor when coring and constructing the TMA. Additionally, the present study observed a broad distribution of HER2 expression in hormone receptor positive breast cancer cases. There is no significant difference in TROP2 expression between clinical receptor status groups of this breast cancer cohort (Fig. 13E). The broad TR0P2 expression of cases across these groupings suggests that clinical hormone or HER2 receptor status should not be used as a surrogate for TR0P2 expression. Figs. 14A-14E contain representative images of quantified HER2 and TR0P2 expression within the same tumor using the multiplex assay.The weak inverse relationship between TR0P2 vs. HER2 levels (Fig. 13C) and tabulation of HER2-TROP2 subgroups in Fig. 15 indicates that certain groups of patients are likely to benefit from one targeted therapy but not the other. Therefore, this multiplex assay measuring TROP2 and HER2 expression is expected to be useful in sequencing of ADC therapies in the metastatic setting or, in the future, selection of the right drug for the right patient with early-stage disease.Example 3e:The present study developed and analytically validated a quantitative multiplex immunofluorescence assay for simultaneous detection of HER2 and TROP2 protein expression in breast cancer. By optimizing antibody clones and titrations and generating cell line-based standard curves, the present study achieved sensitive, linear protein quantification across a wide dynamic range. Strong correlations between multiplex and standard singleplex staining support the specificity and accuracy of this assay. Application to a large cohort of breast cancer cases revealed heterogeneity in HER2 and TROP2 expression, with a weak negative correlation between levels of these two biomarkers.Sensitive quantification of HER2 and TR0P2 could have important therapeutic implications. The activity of HER2-targeted ADCs like T-DXdin low HER2-expressing tumorssuggests current assays are insufficient to capture the full spectrum of HER2 expression relevant for patient selection (as demonstrated in the DAISY HER2 0 trial) (Mosele et al., Nat Med. 2023;29(8):2110-2120). Meanwhile, TROP2-ADCs are approved and demonstrating clinical efficacy in triple-negative breast cancer and other subgroups with recent work showing a relationship between target expression and outcome (Rugo et al., Lancet. 2023;402(10411): 1423- 1433; Rugo et al., J Clin Oncol. 2022;40(29):3365-3376; Bardia et al., J Clin Oncol. Published online February 29, 2024JC02301409; Bardia et al., Ther Adv Med Oncol.2024; 16: 17588359241248336; Spring et al., Oncologist. 2021;26(10):827-834; and Bardia et al., Annals of Oncology. 2021 ;32(9) : 1148-1156). The optimal sequencing of ADCs in the second line metastatic setting is not known. The multiplex assay herein provides a tool for oncologists to consider when deciding how to sequence therapy in patients who may benefit from HER2- vs. TROP2-ADCs based on quantitative biomarker levels.Overall, quantitative multiplexed protein analysis offers new opportunities to dissect biomarker heterogeneity and match patients with targeted therapies. Beyond HER2 and TROP2, this multiplexed approach could be expanded to other ADC targets to assist in treatment decisions. In the era of precision oncology, quantitative immunoassays that capture both the absolute protein level of biomarker expression and the comparative levels within a population moves the field closer to delivery on the promise of personalized therapies.Example 4: Quantitative Diagnostics in Anatomic Pathology and Validation of TROPLEX AssayCurrently, there are already more than seven hundred antibody drug conjugates (ADCs) being tested in clinical trials for treating various cancers, and many cancer types are being targeted in more than one cancer specific antigen. There are multiple cancer types which are treatable by more than one ADC. The mechanism of ADC action is thought to be dependent on the recognition of the antibody target triggering chemotherapeutic uptake into the cells leading to high specificity as a mechanism to bring highly toxic drugs only to cells expressing the target. This approach increases the effective dose while reducing toxicity. Examples of ADCs include Trastuzumab deruxtecan (T-DXd) targeting HER2 and Sacituzumab govitecan (SG) targeting TROP2, which are early approvals both currently used in treating metastatic breast cancer.In treating cancers, it is desirable to use the most effective drug first. The identification of the most effective drug is often a difficult task in practice since drugs from different vendors are rarely compared in the same trial. However, it is in the patients’ interest to know if they are likely to benefit. Therefore, there is a need for novel and effective methods for assessment of ADC targets as well as to determine which ADC should be selected for each patient. The Troplex assay addresses this need.Quantitative immunofluorescence (QIF) methods have been used for many years in research lab. Quantitative chromogenic methods are can also be used in research labs and may even be used in clinical labs, although they generally are less linear and have smaller dynamic range compared to QIF. The CAP / CLIA validation of a High Sensitivity HERZ (HS-HER2) quantitative immunofluorescence assay was developed as a laboratory derived test (LDT) using in the clinical Quantitative Diagnostics in Anatomic Pathology (QDAP) CLIA lab. This HS- HER2 assay allows accurate determination of HERZ protein levels in tumor samples in attomoles / mm2and is planned for eventual use for stratification or selection of patients receiving anti-HER2 therapies.In this study, the present study developed and validated a multiplex immunofluorescence assay with quantitative, standardized assessment of two ADC targets (HER2 and TROP2) where the assay is accompanied by a series of quantitative controls. HER2 protein measurement by the previous analytically validated HS-HERZ assay was used as the criterion standard for HERZ target. However, there is no guideline or reference or predicate device to be used as the criterion standard for TROP2 protein level and herein the present study shows the reportable range and reference interval for the quantitative results of TROP2 target.A new cell line microarray (CMA) with a broad range of HERZ and TR0P2 protein expression was constructed, and these cell line controls allow creation of a standard curve, assessed in attomoles / mm2of protein on a histology slide. It is believed that providing a quantitative test that shows, in attomols / mm2, the amount of HER2 and TROP2 expressed in their tumors is valuable to patients and their caregivers. Using this calibrated standard, the assay precisely determines the level of each ADC target in a quantitative, reproducible manner which could help the oncologists make a patient-specific ADC selection.Finally, there are no established guidelines for validation of quantitative immunofluorescence (QIF) assays. The FDA and CAP are the current organizations that provideguidance on assay validation. Both the FDA and the CAP have published guidance for immunohistochemistry (IHC), but these are based on qualitative assessment or “reading” of chromogenic assays. Thus, even though QIF is similar to IHC, the addition of the quantitative aspects of the assay makes the IHC guidance insufficient. The FDA provides a Guidance to Industry for Bioanalytic Method Validation, which includes quantitative assessment of bioanalytic procedures “such as chromatographic assays (CCs) and ligand binding assays (LB As) that quantitatively determine the levels of drugs, their metabolites, therapeutic proteins, and biomarkers in biological matrices such as blood, serum, plasma, urine, and tissue such as skin.” Given this information and the absence of an FDA guidance on QIF, the present study produced the validation document including parts of the IHC guidance and parts of the Bioanalytic guidance for ligand binding assays.Referring to the test development process for Troplex assay optimization and validation process of Fig. 24 the Troplex assay validation study was established and implemented.Example 4a: Calibrator CMA construction and unit conversionA new calibrator CMA (cell line microarray) called CMA 625 was constructed using 9 cell lines with different HER2 and TROP2 expression levels, including JURKAT HTB-152, TT CRL-1803, DLD-1 #CCL-221, VCaP #CRL2876, BT20 #HTB-19, T47D #HTB-133, ZR-75-1 #CRL-1500, BT483 #HTB-121, and A431 # CRL-1555. The cell lines were procured from ATCC (American Type Culture Collection). Individual cell line was cultured in accordance with the standard culture method provided by ATCC. Cell pellets were produced by culturing cells to the threshold of stationary phase (confluence), frozen and shipped to Protypia for LC-MS / MS for HER2 and TR0P2 protein quantity (data provided in attomoles / ug total protein). A second cell pellet were stored in 70% EtOH and shipped to Array Sciences for CMA production using the same cell lines and constructed 4 master blocks with an expected yield of at least 250 consecutive histology sections per block. Twofold redundancy of 9 cell lines were arranged in four rows randomly as shown in Fig. 27.For the unit conversion, LC-MS / MS values (attomol / ug) of total protein concentration and cell count was provided by Protypia, then the total protein amount per 1,000,000 cells (ug / 106cells) was calculated. Cells of each core on CMA625 were counted and divided by total area of tissue core (mm2 / 106cells) by QuPath software. To convert to ug / mm2, the total proteinamount per 1,000,000 cells was multiplied by the total area of cells per 1,000,000 cells. Relative HER2 and TROP2 protein abundance as determined by LC-MS / MS was reported in attomol / ug of protein. To transform attomol / ug to attomol / mm2, the attomol / ug of both targets were multiplied by the ug / mm2of each cell line. A detailed description of these methods used in the construction of HS-HER2 standard CMA515 is available in Moutafi et.al6 2022. An example conversion of TROP2 protein in BT-20 cell line is also shown in Fig. 27 and full details of all cells line conversions for both HER2 and TROP2 proteins are included in Figs. 35A-35B.Example 4b: Antibody Optimization for Troplex AssayHER2 Primary Antibody Titration and OptimizationIt was observed the optimal concentration of HER2 (clone 29D8) primary antibody as below and the amount of HER2 primary antibody was thus used in the Troplex assay.To determine the optimal antibody concentrations for the assay, a standardization tissue microarray (TMA) was built by extracting 0.6 mm cores from 80 FFPE breast carcinomas seen at Yale Pathology between 1998 and 2011, 10 breast cell lines controls (prepared at Yale), and 10 non-tumor breast tissue cores. Cases were arranged in columns according to their HER2 status by IHC and FISH. HER2 negative (IHC 2+ Not AMP, 1+ and 0) spots were evaluated. Determination of the optimal concentration to maximize antibody sensitivity was performed as described in Rugo et al. (Lancet. 2023;402(10411): 1423-33.).The titration curve uses the top 10% of signal (true signal) and the bottom 10% of signal (non-specific binding or noise) to determine the signal to noise (S / N) ratio of the antibody over a log fold change in primary antibody concentrations. All other factors remained constant to remove bias. Using the HER2 standardization TMA, 7 concentrations of primary antibody were tested over 2 experimental runs. The results of those 7 concentrations are plotted in Fig. 28A. A S / N peak was observed at 1 ug / ml and determined to be the optimal concentration of the HER2 primary antibody.TROP2 Primary Antibody Titration and OptimizationThe same standardization tissue microarray (TMA) described above was used for the TROP2 (clone 2151) antibody titration on Leica BOND RX autostainer. Seven different concentrations of TROP2 primary antibody were tested in Cy3 channel over 2 experimental runswithout Dako Envision+ system. As there is no gold standard or reference for TROP2 protein measurement, all available TMA spots were evaluated to differentiate negative, low, moderate to high TR0P2 expression. The titration curve plotted in Fig. 28B uses the highest 20% of signal (true signal) and the lowest 20% of signal (non-specific binding or noise) to determine the signal to noise (S / N) ratio of the antibody over a log fold change in primary antibody concentrations. Although not the computed peak, based on the visual impression of lower background noise and a wider range of TROP2 intensities detected in the tissue cores of standard TMA, TROP2 antibody concentration at 0.1 ug / ml was determined to be the optimal concentration for the Troplex assay.Example 4c: Assay Validation and Verification of Performance SpecificationsSample Collection and StainingIn the previous HS-HER2 assay validation study, core biopsies of 40 breast cancer cases from 2018 to 2020 were used. BC cases with a minimum 30% of tumor area and dynamic ranges of HER2 IHC scores were selected to represent the full scale seen in practice. For the individual cases, the manual H&E staining was performed on 1 slide and its adjacent section was used for the validated HS- HER2 staining on Leica BOND RX. The detailed procedures for H&E and HS-HER2 staining were described in SOP_QDAP_003_H&E Staining Protocol and SOP_QDAP_001_HS-HER2 Assay Performance on Leica BOND RX.In this Troplex assay validation study, the adjacent serial sections from the same 40 breast cancer cases described above were used. To monitor the instrument performance of autostainer Leica BOND RX and verify Troplex assay performance, the present study included one slide of the calibrator CMA625 as a control in each tray of each staining batch on Leica BOND RXUsing the conditions identified from the optimizations of both HER2 and TROP2 antibodies (see Example 4b), the duplex immunofluorescence (Troplex) assay was tested on 40 selected BC cases with unknown TROP2 results but known for HER2 target levels. It is notable that there are no changes or modification in the usage of biochemicals and staining conditions for HER2 target as in the HS-HER2 assay.Scanning and Image ProcessingH&E images of 40 selected BC cases were scanned at 20X magnification on Aperio AT2 scanner. All QIF slides of control CMAs and 40 BC cases from both HS-HER2 assay and Troplex assay were scanned at 20X magnification on the CyteFinder HT II multiplexed fluorescent imaging platform (RareCyte, serial number: HT-0452201).The CyteFinder imaging platform uses advanced, high speed, multi-channel systems with integrated machine learning algorithm, designed for digital pathology and clinical laboratories like the QDAP lab. Because of its ability to deliver precise measurement and customized software for LDTs, Troplex assay measurements are sensitive and accurate for detecting low levels of HER2 and TROP2 proteins in each molecular compartments of tumor cells in selected BC cases.Image Processing Prior to QuPath AnalysisPyCharm python with preset scripts was used for the following image processing steps:• lossless compression of original images• conversion of QIF images to false-color pseudo-DAB images• changes of fde names to match QIF images with pseudo-DAB images• creating batch-map in “.csv” format to be used with Qymia presetting if neededDevelopment of Qymia extension in QuPathBased on the open source of QuPath software, a molecular compartmentalization software extension called “Qymia” was developed (Robbins, Qymia in QuPath [computer software], 2023. GitHub. Available from: https: / / github.com / snibbor / Qymia-in-QuPath). It allows the users to choose different preset scripts and / or different options for selecting classifiers, tile sizes, measuring parameters, exporting data, etc. It reinstates the concepts of the AQUA software using molecular compartmentalization for quantification in signal divided by area. The AQUA software is now obsolete (no longer commercially supported and updated). The step-by-step quantitative analysis of HER2 and TROP2 scores by Qymia extension are shown in Example 4d below.Example 4d: Quantitative Analysis by QuPath with Qymia ExtensionAnnotation of ROI by the pathologist on pDAB imagesAfter the image processing in PyCharm, create a QuPath project by adding pseudo-DAB images, H&E images and QIF images, batch map, syn map and preset scripts in the same folder for Qymia analysis. Using QuPath software, a board-certified pathologist examines and circles the regions of interest (ROIs) of invasive tumor regions on pseudo- DAB images of individual cases. The pathologist selects the correct region of interest to include only invasive cancer and chooses the ROI to be representative of the entire specimen. If need, an H&E image is also available to assist in the ROI selection. The measurements of target are only in the ROIs defined by the pathologist.Quantitation and Standard Curve Construction of CMAsIn QuPath software with Qymia extension, the QIF images of control CMAs were used to measure HER2 and TR0P2 signals in each cell lines by using TMA dearrayer and threshold prescripts, exported measurement in Qymia scores. CMA Qymia scores in each cell line were analytically normalized by subtracting the average Qymia score of negative control cell line (Jurkat) spots on each CMA. The standard Qymia Quant in Qymia extension allows you to construct the standard curve by regression of normalized CMA Qymia scores on respective amol / mm2of both targets (Figs. 35A-35B).The linear regression equations of each CMA standard curve were used to quantify the protein amount in ROIs of core biopsies in 8-9 BC cases which were stained in the same tray on Leica BOND RX. Figs. 29A-29B shows the standard curves of HER2 protein in 5 cell lines (Jurkat, BT-20, T47D, BT-483, ZR-75-1) and TR0P2 protein in 5 cell lines (Jurkat, VCaP, DLD-1, T47D, BT-20) of one CMA625 slide in a single Troplex run. Different HER2 and TR0P2 protein expression level in standard cell lines of CMA625 were also shown in QIF images (Figs. 30A-30B) respectively.HER2 Protein Measurement in annotated ROIs of WPS SamplesUsing QuPath software, the pathologist-annotated ROIs in each sample were set the class as tumor / invasive breast cancer (InvBC). Qymia extension allows to copy the exact annotated ROIs from each pseudo-DAB images onto their synced QIF images.For the 40 selected BC cases from previous HS-HER2 validation study, the re-assessment of HER2 protein level in Qymia scores was done by using the pre-settings of Qymia Quant forHS-HER2 assay. Then, the HER2 protein amount in each ROIs of 40 BC cases were automatically convert from Qymia scores to amol / mm2, by using the standard curves of CMA controls in their specific staining batches. This data set was used as the analytic results for HER2 target in this Troplex validation study. Follow the detailed procedure of CyteFinder / QuPath analysis method in the Validation of Bridging Study from PM2000 / AQUA to CyteFinder / QuPath for HS-HER2 Assay on Leica BOND RX (SOP-QDAP_006_ Version 1).Thereafter, HER2 protein measurement in 40 BC cases stained by the Troplex assay was carried out by standard Qymia Quant in QuPath software. Using the same ROIs annotated by the board-certified pathologist in HS-HER2 assay, HER2 protein quantities in amol / mm2were exported for individual cases and the scores were averaged if there was more than one ROI per case. Fig. 31 demonstrates quantitative HER2 protein comparison between HER2 measured by the validated HS-HER2 assay and the new Troplex assay. This result shows excellent correlation between the assays with the linear regressions showing R2 value = 0.89 and 0.86 respectively. This shows a highly significant correlation between HER2 measured by the HS-HER2 assay and HER2 measured by the Troplex assay.TROP2 Protein Measurement in annotated ROIs of WPS SamplesSimilarly, TROP2 protein amount in each annotated ROIs of 40 specimens were quantified by standard Qymia Quant in QuPath-Qymia extension as described herein. The present study can measure both targets at the same time and export the measurements in “.csv” file. Taking the average of TROP2 scores in cases with more than one ROIs, the present study quantified TROP2 protein amount in 40 selected BC cases and unit conversion from Qymia scores to amol / mm2was done by using the TROP2 standard curves of CMA625 controls in each Troplex staining batch. HER2 and TROP2 expression within same ROIs per selected breast cancer cases were shown in Figs. 32A-32B. Since there is no predicate device for TROP2 protein measurement, there is no comparison with other assays.Example 4e: Limits of Detection and QuantificationLimit of Detection and Limit of Quantification were defined by the Q2(R1) Validation of analytical procedures: Text and Methodology-Guidance for Industry from the FDA. (https: / / www.fda.gov / regulatory-information / search-fda-guidance-documents / Q2Rl-validation-analytical-procedures-text-and-methodology-guidance-industry). However, in this section the present study defined a LOD and LOQ toward the goal of providing information regarding target detection in patient specimens. The present study found that the coefficients of variation (CVs) of the test can approach that seen in analytic assays for cell line standards but are significantly higher for patient specimens due to inherent variability due to heterogeneity of target expression (rather that assay variability). Furthermore, increased benefit from T-DXd even IHC=3 cases suggesting that the LOL may be unimportant. These findings suggest that the present study should define an LOD and LOQ and an assay dynamic range of leave further, more accurate analytic assessment variables.Limit of DetectionThe FDA defines the limit of detection (LOD) as “The detection limit of an individual analytical procedure is the lowest amount of analyte in a sample which can be detected but not necessarily quantitated as an exact value.” Since the capacity of the current assay to generate an exact measurement is limited by the true analyte (patient tissue) due to target heterogeneity, the present study considered various options. The calculation of LOD of HERZ and TROP 2 biomarkers can be done using a variety of methods. The most stringent method is the “slope method” from the FDAs guidance to industry shown below:LC)D = - s Where,• G = standard deviation of y intercepts• S = Slope of the average calibration curveUsing 6 independent experiments, including 12 cell line sample spots, the following LODs were found:The least objective method and that used for general IHC is just to estimate the signal to noise threshold by pathologist examination and then define that level as the LOD. The present study examined a series of cases processed with the Troplex assay and find that the visual threshold is in the same range as that determined by the signal to noise method.Limit of QuantificationThe limit of quantification is defined as the lowest amount of analyte in a sample which can be quantitatively determined with acceptable precision and accuracy. For analytic assays (like the ligand binding assay) “acceptable precision and accuracy” is defined as a coefficient of variation (CV) below 25%. QIF assays are not at that level of development, the present study has calculated CVs to be in the 10-40% range for QIF due to heterogeneity of target expression in the samples to be measured. So here, for the LOQ a CV<50% was accept as “acceptable precision and accuracy”. Given this information, LOQs of HER2 and Trop2 biomarkers can be calculated using the specific calibration curves (Figs. 33A-33B) as follows:IOCTLOQ = — sWhere,• G = standard deviation of y intercepts• S = Slope of the average calibration curveUsing 6 independent experiments, the following LODs were found:HER2 LOQ =10(17 11= 1093 attomol / mm20.1564987 attomol / mm20.0144Example 4f: Analytical Assessment of Troplex AssayFor this report, the following definitions for HER2 target are applied throughout. Note that HER2 measured by the HS-HER2 assay is considered the predicate device, but comparison to HER2 IHC is also presented in Fig. 37.• True positive = HS-HER2 above LOD and Troplex HER2 Above LOD• True negative = HS-HER2 below LOD and Troplex HER2 Below LOD• False positive = HS-HER2 below LOD and Troplex HER2 Above LOD• False negative = HS-HER2 above LOD and Troplex HER2 Below LODAccuracyAccuracy is defined as the degree to which the result of a measurement, calculation, or specification conforms to the correct value or a standard.The following formula is used to calculate accuracy when compared to standard:Accuracy= (TP+TN) / (FP+FN+TP+TN) x 100Therefore in 40 WTS cases, the accuracy compared to the HS-HER2 assay is as follows: (31 + 4) / (0+5+31+4) x 100 = 88 %Analytical SensitivitySensitivity is defined as the ability of a test to detect a positive where a positive is present. It is also known as “lower limit of detection” i.e., the smallest amount of analyte which can be reliably distinguished from blank. It can be calculated using the formula:Sensitivity = TP / TP+FNIn the selected 40 WTS cases from Yale archives, the following level of sensitivity was achieved:31 / (31+5) x 100 = 86%Analytical SpecificitySpecificity is defined as the ability of a test to detect a negative where a negative is present. It can be calculated by the formula:Specificity = TN / TN+FPIn the selected 40 WTS cases from Yale archives, the following level of specificity was achieved:(4) / (4+0) x 100 = 100%Example 4g: PrecisionPrecision is the reproducibility / repeatability of the assay result over time. It is determined by the ability of the assay to produce the same results when evaluated multiple times within the same run as well as across multiple runs on multiple days and performed by inter-operators.Inter-assay, Intra-operator PrecisionInter-assay precision is a measure of the variance between runs of sample replicates. To calculate inter-assay precision 3 slides were run on 3 separate days with a minimum 1 week wash out period in between. The co-efficient of variation is a measure of precision from repeated measures.It is calculated as follows:% CV = Mean of SD(Means) / Mean of Means x 100Inter-assay %CV of HER2 = 16.49 / 164.32 *100 = 10%Inter-assay %CV of TROP2 = 11.94 / 121.80 *100 = 9.8%Intra-assay PrecisionIntra-assay precision is a measure of variance between data points within an assay. To calculate intra- assay precision 3 slides were run on 3 separate trays of Leica BondRx in a single run.% CV = Mean of SD(Means) / Mean of Means x 100Intra-assay %CV of HER2 = (13.27 / 206.44) *100 = 6.4%Intra-assay %CV of TROP2 = (7.80 / 125.76) *100 = 6.2%Inter-operator PrecisionAs a part of Intra-assay precision test, the same experiment was performed by two operators on the selected specimens with dynamic ranges of HER2 and TROP2 protein expression.Covering low HER2 (IHC scores 0, 1+, 2+ Not Amplified) and high HER2 (IHC scores 2+ & 3+) amplification, the present study chose 4 CMA625 slides and the serial sections of 10 cases out of 40 WTSs used in this validation study. To examine the reproducibility of this Troplex assay, the two operators performed separate auto-staining of selected 10 WTS cases with CMA625 controls at the exact staining condition on Leica BOND RX, then scanned the slides onCyteFinder HT by using the same script and exposure time for the same ROIs annotated by the pathologist and did the QuPath-Qymia analysis.The % CV for each sample is calculated by finding the standard deviation of means of amol / mm2from two data sets of each target generated by two operators, dividing that by the duplicate mean, and multiplying by 100. The average of the individual CVs is reported as the intra-assay CV by inter-operator reproducibility test as follow:% CV for individual case = Mean of SD(Means) / Mean of Means x 100Average %CV of HER2 for 10 selected cases = (17.8 / 214.3)* 100 = 8.3%Average %CV of TROP2 for 10 selected cases = (4.0 / 46.9)* 100 = 8.6%Reportable RangeThis is the range in attomole / mm2of results over which the assay accuracy had been verified.The HS-HER2 assay showed more accurate and objective analytical assessment of HER2 protein expression in HER2 low patients than the legacy IHC test which has a subjective range of “0” to “3+” by the pathologists’ scoring. The previous HS-HER2 assay can detect a single protein target (HER2) with the linearity ranging from 3 attomole / mm2to 23 attomoles / mm2using version 1 cell line standards (CMA515) where each CMA cell line is measured by mass spec.The Troplex Assay uses version 2 of the standard, which is believed to be more accurate since care was taken in harvesting and transporting the cell lines to increase the accuracy of the mass spectrometry measurements. Using this information to Reportable range for this assay was determined as follows:For HER2: the LOD at the low end (105 amol / mm2) to the highest case in the validation set (7184 amol / mm2) represents the reportable range; (400 -7200).For TROP2: the LOD at the low end (907 amol / mm2) to the highest case in the validation set (21966 amol / mm2) represents the reportable range; (900 -22000).Example 4h: Troplex ReportingIn this section, descriptions of reporting forms, as well as some sample forms for clinical use are provided.Report from Lab to the Pathologist of RecordFor each specimen measured in the QDAP lab the laboratory will produce a report for the pathologist to review prior to pathologists’ signout in CoPath. The report to the pathologist will show the Surgical Pathology case number, the patients last name as a second identifier, the attomoles / mm2for HER2 and a representative pseudoDAB image at approximately 20X magnification and the attomoles / mm2for TROP2 and a representative pseudoDAB image. The report will also show the assay performance date and batch number and Leica Bond tray # for the case. The report will also show the LOD for both HER2 and TROP2 and the standards version number. Finally, the report will contain CMA slide number and section number used for the standardization of measurement. The report will be produced as a PDF file and archived in the QDAP lab. An example report is shown in Figs. 39-40.Sample Report from Pathologist to Patient Chart / LIMS and Interpretation NoteSample ReportThe invasive tumor in this sample contains [ ] attomoles of HER2 protein per mm2The invasive tumor in this sample contains [ ] attomoles of TROP2 protein per mm21 [ ]: HER2 protein expression is NOT DETECTED in this tumor. The measured level in “results” above is below the limit of detection of the assay for HER2;2 [ ]: TROP2 protein expression is NOT DETECTED in this tumor. The measured level in “results” above is below the limit of detection of the assay for TROP2;3 [ ]: HER2 Expression protein expression IS DETECTABLE in this tumor. The measured level of HER2 protein in “results” above is above the limit of detection of this analytic assay. This level of HER2 target ranks this patient at the [ ]thpercentile compared to a population of breast cancer tumors.4 [ ]: TROP2 Expression protein expression IS DETECTABLE in this tumor. The measured level of TROP2 protein in “results” above is above the limit of detection of this analytic assay. This level of TROP2 target ranks this patient at the [ ]thpercentile compared to a population of breast cancer tumors.NOTE: The attomole / mm2is nearly always lower for HER2 than TROP2 due the biological properties of breast cancers. Thus, when comparing levels of the targets the comparison should be made between the ranked percentiles in breast cancer populations.Example 5: Real world Retrospective Troplex StudyA real-world retrospective study was performed, which showed continuous statistically significant increased response with increased target concentration for HER2.In this study, 5 leases were collected from Dana-Farber Cancer Institute (DFCI). In all of the cases, the patients received T-DXd in second line treatment or higher. Most of the breast cancer cases were IHC 3+ (60%), but some were lower.Referring to Figs. 42-43, the analysis of the 51 patients showed a continuous statistically significant relationship between amol / mm2of Target and Response measured as time to next treatment (TTNT).Example 6: Troplex Prospective Study on Core Biopsy Tissue from Yale Pathology LabsA prospective study was performed, in which 98 breast cancer cases from Sep’23 to May’24 were used.The study obtained breast cancer core biopsy tissues from the 98 cases. For each case, the tumor sample was stained H&E on the first cut and QIF on second cut. HER2 and TROP2 were measured on each in amol / mm2. Samples from 5 cases were determined to have either insufficient tumor cells or damaged tissue, and were excluded. The results are shown in Figs. 44 and 45A-45B.Referring to Figs. 45A-45B, an inverse relationship between the TROP2 levels and HER2 levels, meaning most patient have more of one target than the other. As such, it is expected that, for most breast cancer patients, one of HER2 or TROP2 should be selected as the first target to produce desirable results. The prospective study also demonstrated that the dynamic range obtained using the method herein are comparable to those obtained using existing methods.Enumerated EmbodimentsEmbodiment 1: A method of treating cancer in a subject in need thereof, the method comprising:determining a first level of a first cancer-specific antigen in a cancer sample of the subject; determining a second level of a second cancer-specific antigen in the cancer sample; and administering to the subject: a first antibody-drug conjugate (ADC) targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value and the second level is equal to or lower than a second predetermined value, or a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.Embodiment 2: The method of Embodiment 1, wherein the first level, the first predetermined value, and / or the third predetermined value are expressed as absolute levels of the first cancer-specific antigen, and / or the second level, the second predetermined value, and / or the fourth predetermined value are expressed as absolute levels of the second cancer-specific antigen.Embodiment 3: The method of Embodiment 1, wherein the first level, the first predetermined value, and / or the third predetermined value are expressed as a percentile rank of the levels of the first cancer-specific antigen in a collection of samples of the cancer, and / or the second level, the second predetermined value, and / or the fourth predetermined value are expressed as a percentile rank of the level of the second cancer-specific antigen in the collection of samples of the cancer.Embodiment 4: The method of Embodiment 3, wherein the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.Embodiment 5: The method of any one of Embodiments 1-4, wherein the first level and / or the second level is determined by a quantitative immunofluorescence method or a quantitative chromogenic method.Embodiment 6: The method of Embodiment 5, wherein the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines the first level and the second level in a same immunostaining assay.Embodiment 7: The method of any one of Embodiments 1 -6, wherein the cancer is breast cancer.Embodiment 8: The method of any one of Embodiments 1-7, wherein the first cancerspecific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancerspecific antigen is tumor associated calcium signal transducer 2 (TR0P2).Embodiment 9: The method of any one of Embodiments 1-8, further comprising collecting the cancer sample from the subject.Embodiment 10: The method of any one of Embodiments 1-9, wherein the subject is a human.Embodiment 11 : A method of predicting an outcome of a treatment of a cancer with a sample from the cancer, or a method of performing an in vitro examination of the sample, the method comprising: determining a first level of a first cancer-specific antigen in the sample; determining a second level of a second cancer-specific antigen in the sample; making a prediction that: the cancer is more susceptible to a first ADC targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value and the second level is equal to or lower than a second predetermined value, or the cancer is more susceptible to a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.Embodiment 12: The method of Embodiment 11, wherein the first level, the first predetermined value, and / or the third predetermined value are expressed as absolute levels of the first cancer-specific antigen, and / or the second level, the second predetermined value, and / or the fourth predetermined value are expressed as absolute levels of the second cancer-specific antigen, wherein the absolute levels are optionally expressed as amount per area as determined by a quantitative imaging method, optionally expressed as attomole / mm2.Embodiment 13: The method of Embodiment 11, whereinthe first level, the first predetermined value, and / or the third predetermined value are expressed as a percentile rank of the levels of the first cancer-specific antigen in a collection of samples of the cancer, and / or the second level, the second predetermined value, and / or the fourth predetermined value are expressed as a percentile rank of the level of the second cancer-specific antigen in the collection of samples of the cancer.Embodiment 14: The method of Embodiment 13, wherein the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.Embodiment 15: The method of any one of Embodiments 11-14, wherein the first level and / or the second level is determined by a quantitative immunofluorescence method or a quantitative chromogenic method.Embodiment 16: The method of Embodiment 15, wherein the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines the first level and the second level in a same immunostaining assay.Embodiment 17: The method of any one of Embodiments 11-16, wherein the cancer is breast cancer.Embodiment 18: The method of any one of Embodiments 11-17, wherein the first cancerspecific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancerspecific antigen is human trophoblast cell-surface antigen (Trop2).Embodiment 19: The method of any one of Embodiments 11-18, further comprising collecting the sample from a subject.Embodiment 20: The method of Embodiment 19, wherein the subject is a human.Embodiment 21 : A method of constructing a cancer antigen level standard in a cancer type, the method comprising: determining the levels of a first cancer-specific antigen in a collection of cancer samples of the cancer type; plotting a frequency distribution of the first cancer-specific antigen levels such that each given level of the first cancer-specific antigen corresponds to a percentile rank of the first cancerspecific antigen levels; determining the levels of a second cancer-specific antigen in the collection of cancer samples; andplotting a frequency distribution of the second cancer-specific antigen levels such that each given level of the second cancer-specific antigen corresponds to a percentile rank of the second cancer-specific antigen levels.Embodiment 22: The method of Embodiment 21, wherein the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.Embodiment 23: The method of any one of Embodiments 21-22, wherein the levels of the first cancer-specific antigen and / or the levels of the second cancer-specific antigen are determined by a quantitative immunofluorescence method or a quantitative chromogenic method.Embodiment 24: The method of Embodiment 23, wherein the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines a first level of the first cancer-specific antigen and a second level of the second cancer-specific antigen of a given sample in the collection of cancer samples in a same immunostaining assay.Embodiment 25: The method of any one of Embodiments 21-23, wherein the cancer type is breast cancer.Embodiment 26: The method of any one of Embodiments 21-25, wherein the first cancerspecific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancerspecific antigen is human trophoblast cell-surface antigen (Trop2).The foregoing outlines features of several embodiments so that those skilled in the art may better understand the aspects of the present disclosure. Those skilled in the art should appreciate that they may readily use the present disclosure as a basis for designing or modifying other processes and structures for carrying out the same purposes and / or achieving the same advantages of the embodiments introduced herein. Those skilled in the art should also realize that such equivalent constructions do not depart from the spirit and scope of the present disclosure, and that they may make various changes, substitutions, and alterations herein without departing from the spirit and scope of the present disclosure.

Claims

CLAIMSWhat is claimed is:

1. A method of treating cancer in a subject in need thereof, the method comprising: determining a first level of a first cancer-specific antigen in a cancer sample of the subject; determining a second level of a second cancer-specific antigen in the cancer sample; and administering to the subject: a first antibody-drug conjugate (ADC) targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value and the second level is equal to or lower than a second predetermined value, or a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.

2. The method of claim 1, wherein the first level, the first predetermined value, and / or the third predetermined value are expressed as absolute levels of the first cancer-specific antigen, and / or the second level, the second predetermined value, and / or the fourth predetermined value are expressed as absolute levels of the second cancer-specific antigen.

3. The method of claim 1, wherein the first level, the first predetermined value, and / or the third predetermined value are expressed as a percentile rank of the levels of the first cancer-specific antigen in a collection of samples of the cancer, and / or the second level, the second predetermined value, and / or the fourth predetermined value are expressed as a percentile rank of the level of the second cancer-specific antigen in the collection of samples of the cancer.

4. The method of claim 3, wherein the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.

5. The method of any one of claims 1 -4, wherein the first level and / or the second level is determined by a quantitative immunofluorescence method or a quantitative chromogenic method.

6. The method of claim 5, wherein the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines the first level and the second level in a same immunostaining assay.

7. The method of any one of claims 1-6, wherein the cancer is breast cancer.

8. The method of any one of claims 1-7, wherein the first cancer-specific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancer-specific antigen is tumor associated calcium signal transducer 2 (TROP2).

9. The method of any one of claims 1-8, further comprising collecting the cancer sample from the subject.

10. The method of any one of claims 1-9, wherein the subject is a human.

11. A method of predicting an outcome of a treatment of a cancer with a sample from the cancer, or a method of performing an in vitro examination of the sample, the method comprising: determining a first level of a first cancer-specific antigen in the sample; determining a second level of a second cancer-specific antigen in the sample; making a prediction that: the cancer is more susceptible to a first ADC targeting the first cancer-specific antigen if the first level is equal to or higher than a first predetermined value and the second level is equal to or lower than a second predetermined value, or the cancer is more susceptible to a second ADC targeting the second cancer-specific antigen if the second level is equal to or higher than a third predetermined value and the second level is equal to or lower than a fourth predetermined value.

12. The method of claim 11 , wherein the first level, the first predetermined value, and / or the third predetermined value are expressed as absolute levels of the first cancer-specific antigen, and / or the second level, the second predetermined value, and / or the fourth predetermined value are expressed as absolute levels of the second cancer- specific antigen, wherein the absolute levels are optionally expressed as amount per area as determined by a quantitative imaging method, optionally expressed as attomole / mm2.

13. The method of claim 11, wherein the first level, the first predetermined value, and / or the third predetermined value are expressed as a percentile rank of the levels of the first cancer-specific antigen in a collection of samples of the cancer, and / or the second level, the second predetermined value, and / or the fourth predetermined value are expressed as a percentile rank of the level of the second cancer-specific antigen in the collection of samples of the cancer.

14. The method of claim 13, wherein the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.

15. The method of any one of claims 11-14, wherein the first level and / or the second level is determined by a quantitative immunofluorescence method or a quantitative chromogenic method.

16. The method of claim 15, wherein the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines the first level and the second level in a same immunostaining assay.

17. The method of any one of claims 11-16, wherein the cancer is breast cancer.

18. The method of any one of claims 1 1-17, wherein the first cancer-specific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancer-specific antigen is human trophoblast cell-surface antigen (Trop2).

19. The method of any one of claims 11-18, further comprising collecting the sample from a subject.

20. The method of claim 19, wherein the subject is a human.

21. A method of constructing a cancer antigen level standard in a cancer type, the method comprising: determining the levels of a first cancer-specific antigen in a collection of cancer samples of the cancer type; plotting a frequency distribution of the first cancer-specific antigen levels such that each given level of the first cancer-specific antigen corresponds to a percentile rank of the first cancerspecific antigen levels; determining the levels of a second cancer-specific antigen in the collection of cancer samples; and plotting a frequency distribution of the second cancer-specific antigen levels such that each given level of the second cancer-specific antigen corresponds to a percentile rank of the second cancer-specific antigen levels.

22. The method of claim 21, wherein the collection of samples is a collection of cancer cell lines and / or primary cancer cells derived from patients of the cancer.

23. The method of any one of claims 21-22, wherein the levels of the first cancer-specific antigen and / or the levels of the second cancer-specific antigen are determined by a quantitative immunofluorescence method or a quantitative chromogenic method.

24. The method of claim 23, wherein the quantitative immunofluorescence method or the quantitative chromogenic method is a multiplex method that determines a first level of the firstcancer-specific antigen and a second level of the second cancer-specific antigen of a given sample in the collection of cancer samples in a same immunostaining assay.

25. The method of any one of claims 21-23, wherein the cancer type is breast cancer.

26. The method of any one of claims 21-25, wherein the first cancer-specific antigen is human epidermal growth factor receptor 2 (HER2), and / or the second cancer-specific antigen is human trophoblast cell-surface antigen (Trop2).

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